Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Felix, Demian Ferreira
Master of Science - MSc
University of British Columbia
Background: Kidney stone disease (KSD) is a worldwide metabolic disorder, that affects about 12% of the world population at some stage of life, representing a financial burden for health systems. The prevalence of urolithiasis is increasing in the past decades, despite progress in the surgical procedures to remove the stones, there is a recurrence rate after the intervention, and there is no definitive cure for it. In the past decades, the role of intestinal microbiota regarding KSD pathology has been gradually unravelled. Oxalate-degrading bacteria and short-chain fatty acid (SCFA) producing microorganisms have been shown to have important roles in crystal formation through direct calcium oxalate breakdown or as inducers of immune responses capable of inhibiting crystal formation in the kidneys. Experimental approach: In order to test the properties of prebiotics in stone formation physiology, we used an in vivo mouse model administering four different formulated diets. A control diet, a sodium oxalate diet to stimulate stone formation, an inulin diet to stimulate SCFA-producing microorganisms, and a tributyrin diet to act as a direct source of butyrate, a specific type of SCFA that we have previously shown to be lacking in kidney stone patients. Results: Results indicated that the sodium oxalate diet reduced the overall mice microbial alpha diversity and the variability of bacterial groups responsible for SCFA production. It also increased oxalate concentrations in the urine and caused crystal formation in the kidney. Furthermore, an inulin diet was able to promote the proliferation of SCFA-related microbiota and SCFA concentrations in the gut, which resulted in reduced oxalate amounts in the urine, therefore, contributing to reducing the risk of stone formation. Tributyrin supplementation did not promote any significant effect. Conclusions: This study corroborates previous research indicating that dietary supplements like inulin are potential prebiotic candidates to promote gut homeostasis, oxalate absorption regulation, and modulate SCFA-related microbial population and SCFA production in the intestine.
HOW GUT MICROBIOME CORRELATES WITH OXALATE, BUTYRATE AND KIDNEY STONES FORMATION by Demian Ferreira Felix B.Sc., The Pontifical Catholic University of Minas Gerais, 2004 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) November 2022 © Demian Ferreira Felix, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: How gut microbiome correlates with oxalate, butyrate and kidney stones formation submitted by Demian Ferreira Felix in partial fulfillment of the requirements for the degree of Master of Science in Experimental Medicine Examining Committee: Dr. Dirk Lange, Associate Professor, Urologic Sciences, UBC Supervisor Dr. Ben Chew, Associate Professor, Urologic Sciences, UBC Supervisory Committee Member Dr. Genelle Healey, Posdoctoral Research Fellow, Pediatrics, BC Children's Hospital, UBC Supervisory Committee Member Dr. Gregory E Tasian, Pediatric Urologist, Urology, Children's Hospital of Philadelphia Additional Examiner iii Abstract Background: Kidney stone disease (KSD) is a worldwide metabolic disorder, affecting about 12% of the world population at some stage of their life, representing a financial burden for health systems. The prevalence of urolithiasis is increasing in the past decades, despite progress in the surgical procedures to remove the stones, there is a recurrence rate after intervention, and there is not a definitive cure for it. In the past decades, the role of intestinal microbiota regarding KSD pathology has been gradually unraveled. Oxalate degrading bacteria and short-chain fatty acid (SCFA) producing microorganisms have shown to have important roles in crystal formation through direct calcium oxalate break down or as inducers of immune responses capable of inhibiting crystal formation in the kidneys. Experimental approach: In order to test the properties of prebiotics in stone formation physiology, we used an in vivo mouse model administering four different formulated diets. A control diet, a sodium oxalate diet to stimulate stone formation, an inulin diet to stimulate SCFA producing microorganisms, and a tributyrin diet to act as a direct source of butyrate, a specific type of SCFA that we have previously shown to be lacking in kidney stone patients. Results: Results indicated that sodium oxalate diet reduced the overall mice microbial alpha diversity and the variability of bacterial groups responsible for SCFA production. It also increased oxalate concentrations in the urine and caused crystal formation in the kidney. Furthermore, an inulin diet was able to promote the proliferation of SCFA related microbiota and SCFA concentrations in the gut, which resulted in reduce oxalate amounts in the urine, therefore, contributing to reducing the risk of stone formation. Tributyrin supplementation did not promote any significant effect. Conclusions: This study corroborates previous research indicating that dietary supplements like inulin are potential prebiotic candidates to promote gut homeostasis, oxalate absorption regulation, and modulate SCFA related microbial population and SCFA production in the intestine. iv Lay summary The formation of small crystals in the kidneys leads to kidney stone disease. It is usually very painful to expel these stones through the urine, and the symptoms can last for weeks. Once formed, additional stones usually recur within a certain time. Surgical procedures available to treat this disease cannot definitively cure it, and often, a patient requires more than one surgery to help treat the disease. We studied the causes of stone formation and the differences between kidney stone patients and healthy people. Recently scientists discovered that gut bacteria are responsible for maintaining health and research suggests that specific foods are responsible for helping the good bacteria in our gut to promote health. Comparing bacteria from healthy people and stone patients, we observed that foods containing inulin fibre could help the gut bacteria produce a metabolite that will help to reduce the formation of the crystals in the kidneys. v Preface Demian Ferreira Felix was involved in designing, conducting and analyzing the research experiments under the direct guidance of Dr. Dirk Lange and Dr. Ben Chew with assistance from Dr. Genelle Healey, Dr. Aaron Miller, and with the help of Dr. Lange's Lab members at the University of British Columbia. All diets were formulated in collaboration with Dr. Genelle Healey, a Dietitian in the Vallance Lab (BC Children's Hospital) as well as Dr. Tina Herfel, a nutritionist at Envigo. The DNA extraction, sequencing and data analysis were performed by Dr. Aaron Miller working for the Learner Research Institute /Cleveland Clinic, US. Regarding oxalate measurement, the optimization of protocols related to cleaning up samples and setting up HPLC/MS equipment were performed with the aid of the chemist Hans Adomat, from the Prostate Centre Institute. Post-Doctoral fellow Dr. Alina Reicherz, from Dr. Lange’s Laboratory, performed kidney histological embedding, sectioning and staining. All animal procedures describe herein were approved by the University of British Columbia Animal Care Committee under protocol A18-0356. vi Table of Contents Abstract ................................................................................................................................................... iii Lay Summary ......................................................................................................................................... iv Preface ....................................................................................................................................................... v Table of Contents .................................................................................................................................... vi List of Tables ......................................................................................................................................... viii List of Figures ......................................................................................................................................... ix List of Abbreviations .............................................................................................................................. xi Acknowledgements................................................................................................................................ xii Dedication ............................................................................................................................................. xiii Chapter 1: Background ........................................................................................................................... 1 1.1 Kidney Stones Disease ................................................................................................................... 1 1.1.1 Epidemiology ............................................................................................................................ 1 1.1.2 Public health concerns ............................................................................................................. 3 1.1.3 Types of kidney stone ............................................................................................................... 3 1.1.4 Current available treatments .................................................................................................. 7 1.1.5 Dietary factors that modify kidney stone risk ....................................................................... 8 1.1.6 Hyperoxaluria and the role for intestinal bacteria in kidney stone formation................. 10 1.1.7 Intestinal absorption of oxalate and butyrate producer microbiota ................................. 15 1.1.8 Short chain fatty acid production ......................................................................................... 17 1.2 Rationale for thesis project ......................................................................................................... 17 Chapter 2: Materials and Methods ...................................................................................................... 21 2.1 In vivo model .................................................................................................................................. 21 vii 2.2 Analytical chemistry ..................................................................................................................... 25 2.3 Molecular biology methods .......................................................................................................... 26 2.4 Histological methods .................................................................................................................... 28 Chapter 3: Results .................................................................................................................................. 29 3.1 Impact of diet on urinary oxalate levels ...................................................................................... 29 3.2 Impact of high oxalate diet on intestinal microbiome composition .......................................... 30 3.3 Impact of high oxalate, inulin and tributyrin diets on intestinal microbiome composition ... 34 3.4 SCFA profile differences between groups for stool and cecal samples ..................................... 43 3.4.1 Correlation between SCFA profiles and ASVs .................................................................. 49 3.5 Histology ........................................................................................................................................ 51 3.6 Food and water consumption by animals ................................................................................... 52 Chapter 4: Discussion ............................................................................................................................ 54 Chapter 5: Conclusions and Future Directions ................................................................................... 60 Bibliography ........................................................................................................................................... 61 viii List of Tables Table 1: Nutritional components of Envigo formulated diets .................................................................. 22 Table 2: Experimental diet plan for 5 weeks ............................................................................................ 23 Table 3: Sample collection plan ............................................................................................................... 24 Table 4: The number of ASVs associated with SCFA ............................................................................. 50 ix List of Figures Figure 1: Scheme representation of extracellular events during nephrolithiasis ..................................... 20 Figure 2: Oxalate levels in mouse urine after consuming the control, sodium oxalate, inulin and tributyrin diets .......................................................................................................................................................... 29 Figure 3: Alpha diversity shift in mouse stool microbiota after consuming the control (Control T1, Control T2, Treated T1) and sodium oxalate diets (Treated T2) between time point one (T1) and time point two (T2) .......................................................................................................................................... 30 Figure 4: Beta diversity shift in mouse stool microbiota after consuming the control (Control T1, Control T2, Treated T1) and sodium oxalate diets (Treated T2) between time point one (T1) and time point two (T2)........................................................................................................................................................... 31 Figure 5: Mice stool microbiota relative abundance differences after control and sodium oxalate diet treatments ................................................................................................................................................. 32 Figure 6: Mice stool microbiota relative abundance differences at lowest assigned taxonomic distribution level after base chow and sodium oxalate diet treatments ....................................................................... 33 Figure 7: Alpha diversity values of mice stool microbiota after four diet treatments. P value reflects global ANOVA .................................................................................................................................................... 34 Figure 8: Beta diversity values for stool samples after four diet treatments. P value reflects global ANOVA .................................................................................................................................................... 35 Figure 9: Mice stool microbiota relative abundance differences at the phylum level after four diet treatments comparing the start point (base chow) and final point (Control, Inulin, Oxalate, Tributyrin) within the same mice group ..................................................................................................................... 36 Figure 10: Mice stool microbiota relative abundance differences at the lowest assigned taxon level after control and sodium oxalate diet treatments.............................................................................................. 37 Figure 11: Shows differential abundance on mice stool microbiota after consuming base chow (Control) and Inulin at the endpoint for different mice treatments .......................................................................... 38 Figure 12: Alpha diversity values from cecal content after the four diet treatments. P value reflects global ANOVA .................................................................................................................................................... 39 Figure 13: Beta diversity shift on mice cecal content microbiota after consuming base chow (Control T1, Control T2, Treated T1) and sodium oxalate diet (Treated T2) between time point one and time point two .................................................................................................................................................................. 40 Figure 14: Mouse cecal content microbiota relative abundance differences at the phylum level after four diet treatments at the final experimental time point ................................................................................. 41 x Figure 15: Number of ASVs/ Taxon abundance in mouse cecal content microbiota after consuming control and inulin diet .............................................................................................................................. 42 Figure 16: Final concentration of acetic acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B) .............................................................................. 43 Figure 17: Final concentration of butyric acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B) .............................................................................. 44 Figure 18: Final concentration of isovaleric acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B) .......................................................................... 45 Figure 19: Final concentration of lactic acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B) .............................................................................. 46 Figure 20: Final concentration of propionic acid in cecal content samples, and change in acetic acid in stool before and after treatment in stool samples ..................................................................................... 47 Figure 21: Final concentration of succinic acid in cecal content samples, and change in acetic acid in stool before and after treatment in stool samples ..................................................................................... 48 Figure 22: Number of ASV's per lowest assigned taxonomy that exhibited a significant, positive correlation between ASV abundance and SCFA concentration for acetic, butyric, isovaleric, lactic, propionic and succinic acids .................................................................................................................... 49 Figure 23: Thin sections of the kidney cortex from animals on control and sodium oxalate diets. Arrows indicate crystal location ........................................................................................................................... 51 Figure 24: Thin sections of the kidney cortex from animals on regular control) (K3) and sodium oxalate diets (K24, K25). Arrows indicate crystal location .................................................................................. 52 Figure 25: Average food consumption over time for mice on the four different dietary treatments ....... 53 Figure 26: Average water consumption over time for mice on the four different dietary treatments ...... 53 xi List of Abbreviations ASV – Amplicon Sequence Variant CaOx - Calcium Oxalate CUA - Canadian Urological Association DIDS - 4,4' diiso-thiocyanatostilbene-2,2'-disulfonic acid DNA- Deoxyribonucleic acid HPLC/MS - High Performance Liquid Chromatography/ Mass Spectometry IBD - Inflammatory Bowel Disease KSD - Kidney Stone Disease MAG - Metagenome Assembled Genomes OTU - Operational Taxonomic Unit PCNL - Percutaneous Nephrolithotomy PCR - Polymerase Chain Reaction PHY - Primary Hyperoxaluria PTH - Parathyroid Hormone RIRS - Retrograde Intra-renal Surgery RNA - Ribonucleic Acid ROS - Reactive Oxygen Species SCFA - Short-Chain Fatty Acids SPE - Solid Phase Extraction SWL - Shockwave Lithotripsy TEER - trans epithelial electrical resistance THP - Tamm-Horsfall Glycoproteins USA- United States of America xii Acknowledgements I would like to thank my supervisor Dr. Dirk Lange for his vision, availability and patience throughout my Master degree. His generosity and perseverance kept me on track to conclude my thesis. I hope that the contribution of my research can be as meaningful to the Lab as meeting him has been to my life. The counsel and experience of Dr. Genelle Healey was fundamental to develop the experimental diet model and in vivo setup, her contributions to this thesis were very significant for the optimum conclusion of this work. I would like to thank Dr. Ben Chew for all his support and valuable advice towards the improvement of my thesis. I was very fortunate to have such great Lab colleagues like Sara, Amal, Khaled, Sahand, Kymora, Donald, Alina, Roman, Sarah, Dalia and Samin, they have contributed to my scientific and personal progress. xiii Dedication Dedicated to Marisa, Vicente and Ariane for supporting and believing in me since always. Dedicated to Andreia who always inspired me to be a better version of myself. Dedicated to all the people who suffer from kidney stone disease, hoping to improve their life quality and treatment. 1 1 Background 1.1 Kidney Stone Disease Kidney stone disease is a metabolic condition related to mineral precipitation in the urinary system1. This process usually starts in the kidney but can also happen in other portions of the urinary tract, including the bladder1. Small mineral clusters formed in the kidney can either remain attached to the tissue causing mineral plaques or detach from it moving along the urinary tract.1,2. When crystals are not naturally cleared by peristalsis they can become lodged in one particular area causing an obstruction that causes tissue damage, inflammation, and severe pain to the patient1,2. Initially stone formation is asymptomatic, but when specific areas become obstructed, a variety of effects such as renal colic, urinary tract infections, hematuria, and kidney disease can occur. There is not any definitive cure, and it is a major economic burden to the health care system1,3. 1.1.1 Epidemiology Kidney stone formation varies in different regions of the world. It appears to have higher incidence in the western hemisphere, with incidences of KSD ranging from 10-12% in Canada, 13-15% in the USA. The incidence in the eastern hemisphere appears to be lower overall at 1-5%, while it is 5-9% in Europe3. The age group affected by urolithiasis (deposits made of minerals inside the kidneys) and bladder stones varies according to geographical location. In the Afro-Asian stone forming region the disease affects all age groups from 1 to 70 years old, with a male: female ratio of 2:13. In the USA, individuals between 60 to 70 years old have the highest kidney stone incidence4. That said, a growing number of studies show that the prevalence of kidney stones is also increasing among children, adolescents and women5,6 . 2 Recent studies have shown that the overall prevalence of kidney stones in the USA population has increased from 5.2% to 8.2% in about one decade, and the occurrence of the disease in this country is higher in males (10.6%) than females (7.1%)6,7. Furthermore, it occurs more frequently in white caucasians than in blacks, having a 4:1 Caucasian:Black ratio in the USA and Brazil5. This difference is probably related to dietary factors rather than inborn racial genetic background because the prevalence of stone disease increases in black Americans when they adopt Westernized dietary habits3. In Canada, according to the Canadian Urological Association (CUA), approximately one in ten Canadians will develop kidney stones8. In the Indian population, 12% are expected to have urinary stones, of which 50% may end up with a loss of kidney function3. While the overall global incidence of kidney stone disease is already high, it continues to increase. Studies have shown that the prevalence of stone disease has increased in Japan, Italy, Germany, Scotland, Spain, Sweden4,9, and some Asian countries such as Saudi Arabia; with increasing risks up to 20.1%10. The higher incidence of stone formation in hot climate countries is likely related to high perspiration/dehydration, low urinary output, and low fluid intake. This is particularly evident in the USA, where the incidence is greater along the North American stone belt (states of Virginia, North Carolina, Georgia, Tennessee, and Kentucky) region, which is an area where temperatures tend to be higher. Studies have shown a west-east/north-south stone formation gradient indicating the highest kidney stone prevalence in the south-eastern USA3. Along the same lines, the Afro-Asian (Sudan, Egypt, Saudi Arabia, Arab Emirates, Iran, Pakistan, India, Myanmar, Thailand, and Indonesia to the Philippines) stone belt is also characterized by hot weather, although this is not the only associated factor as the high consanguinity among ethnic groups living in those regions may play a genetic factor related to stone disease occurrence3. Interestingly, another factor relating to hyperoxaluria risk may be the absence of Oxalobacter formigenes, an oxalate degrading gut bacteria. This taxon has been shown to be related to a higher kidney stone risk in the north Indian population as well in other countries 3,38. 3 Over the last 10 years, research has shown an escalation in the frequency of calcium oxalate and calcium phosphate stones, including in the eastern hemisphere where they have been historically less common than uric acid and infection-related stones3. Worldwide kidney stones affect about 12% of the world population at some stage of their lives. There is no doubt that the prevalence of urolithiasis is increasing in both developed and developing countries4,5,6. Changes in dietary habits, environmental climate changes, and lack of physical activity are probably associated with this prevalence1. This underscores a significant need for the development of new strategies to treat and prevent kidney stone formation. 1.1.2 Public health concerns Kidney stone disease is a risk factor for kidney failure, bone fracture, cardiovascular disease, and asthma23. Diabetes mellitus and hypertension are also associated with stone formation1,8. Crohn's disease, renal tubular acidosis, and primary hyperparathyroidism are also conditions that increase calcium stone formation3,4. There is a significant economic concern regarding the cost related to treat kidney stone patients and also the lost time off work. Kidney stone disease is estimated to have a direct healthcare cost exceeding $5 billion USD annually in the USA alone7,11. With the increase in incidence of stone disease, the cost is expected to increase by an additional 1.24 billion dollars by 2030, as the rise of diabetes and obesity, conditions related to stone formation, also rise8. The relapse rate of secondary stone formation is estimated to be between 30-50% within 10 years of first presentation, and 75% within 20 years1,8. 4 1.1.3 Types of kidney stones Nephrolithiasis is the technical term for the condition of forming crystals on the urinary system. Stone formation initiate with urine supersaturation in conditions such as hyperoxaluria. The high concentration of solute (usually salts and minerals) causes oxidative stress on the apical layer of kidney epithelial cells, leading to cell injury and membrane rupture, creating the environment to crystal nucleation. The mineral transformation from liquid to a solid phase is regulated by pH and particular concentrations of calcium, phosphorus, uric acid, oxalate, cystine and water in urine. Constitutes of the blood as epithelial and red blood cells, minerals and urinary casts can work as nucleating centres in the nucleation phase (Figure 1)1. Once nucleus is formed crystal growth and the following aggregation takes place. From this point on, crystals interact with cells and start to adhere to the basal membrane, creating the foundation for stone formation2. Urinary stones are composed of a noncrystalline phase (organic material) and crystals. The main organic components of the stone are proteins (64%), non-amino sugars (9.6%), hexosamine such as glucosamine (5%), water (10%), and inorganic ash (10.4%)2. The organic phase is composed of glycosaminoglycans, lipids, carbohydrates, and proteins. This phase plays a role by promoting or inhibiting kidney stone development. Cell membrane phospholipids, as part of the organic matrix, promote the formation of calcium oxalate and calcium phosphate stones. Proteins present in the urine can help or inhibit crystals to precipitate, with albumin being the most present protein in the organic matrix2,66. To clarify which factors are involved in stone formation, it is important to know the main types of stone found in patients as, in some cases, dietary habits can be related to a specific stone type. Five basic types of kidney stones can be classified based on their mineral composition and pathogenesis, these include calcium stones, struvite or magnesium ammonium phosphate stones, uric acid stones (urate), cystine stones and drug induced stones2. 5 Calcium stones are found in the majority of kidney stones (80%) and are composed of calcium oxalate (CaC2O4.H2O) and/or calcium phosphate (CaHPO4.H2O) at different composition rates, being the CaOx monohydrate more thermodynamically stable when compared with the dihydrate CaOx stone1,2. Some dietary habits can be associated with this kind of stone. High salt consumption leads to supersaturation of the blood, which increases the chances of CaC2O4 precipitation. In addition, calcium consumption can affect calcium oxalate (CaOx) formation because calcium typically binds to oxalate in the gastrointestinal tract making it insoluble and therefore unavailable to be absorbed by intestinal cells. In the same line of thinking, previous studies show that calcium is absorbed in the small intestine, and oxalate is absorbed passively in the large bowel. If the calcium consumption is low, some will be absorbed on the initial portions of the gut and little will be available in the large intestine to bind to oxalate and prevent its passively absorption. As oxalate crosses the intestinal epithelium, it enters the bloodstream and subsequently can be accumulated in the kidneys, increasing the lithogenic risk10. Any factor capable of altering the urine pH might also play a role in stone formation as urinary pHs between 5.0 to 6.5 can promote CaOx precipitation and an alkaline pH higher than 7.5 favours CaP formation2. Magnesium ammonium phosphate stones (struvite stones) represent 10-15% of occurring stones and is frequently associated with urinary tract infections (UTI). The link between UTI and stone formation exists as some uropathogens like Proteus mirabilis produce an enzyme called urease which is capable of cleaving urea to ammonia (NH3) and carbonic oxide (CO2). The ammonia is transformed to ammonium (NH4+) and the CO2 is transformed in carbonate (CO32-) turning the urine alkaline (pH>7), which is the ideal condition for phosphate precipitation2,70. Uric acid stones represents 3-10% of all kidney stones and occur when urine pH is below 5.5 and when uric acid is too high. Uric acid can be the outcome of a diet rich in purines, found mainly in organ meats, anchovies, beer and gravy. Increased uric acid levels in urine might lead to hyperuricosuria and later uric acid stone formation2 . 6 Cystine stones represents less than 2% of kidney stone cases. They are caused by an autosomal recessive disorder of the rBAT gene on chromosome 2. This disorder causes low absorption of cystine in the kidneys, allowing it to leak into the urine, and as cystine does not dissolve in urine it precipitates to form cystine stones. It is worth considering that CaOx depositions in the kidneys up regulate the expression and synthesis of macromolecules that can promote inflammation, indicating that there is an immune response towards these mineral depositions43. Important inhibitors and promoters also play a role in crystallization. Osteopontin, a phosphorylated glycoprotein initially found in bone, binds to hydroxyapatite and regulates ectopic calcium deposition. Besides its mineralization, properties it also plays an important role in immune responses with studies revealing that it can modulate commensal microbiota through stimulation of T cell receptors and intraepithelial lymphocytes.71 Osteopontin is also implicated in macrophage migration and immune response modulation, acting as both an inhibitor and promoter of crystal formation depending of immune response variables71. Most of the crystals attached to epithelial cells are thought to be digested by macrophages and/or lysosomes inside cells and then cleared in the urine32. Urolithiasis could be reduced by preventing supersaturation, thus treatments targeted to inhibit the nucleation process are good approaches to control stone formation2. Utilizing a knockout Tamm-Horsfall glycoproteins (THP) gene mice model via embryonic stem cells resulted in spontaneous formation of calcium crystals in adult kidneys showing that THP has critical urinary inhibitor role in human nephrolithiasis31. Other studies have shown that kidney stone patients had 32% lower THP content compared with controls and THP sialic acid content was also lower by 29% and 24% in male and female kidney stone formers.72,73 Interestingly, THP is the most abundant urinary protein, interacting with bacteria as well as host immune cells, such as neutrophils and uropathogenic Escherichia coli (UPEC). Therefore, it has the 7 capacity to mediate immune responses towards uropathogens in the urine. This interaction can be potentially relevant when it comes to struvite crystal formation derived from Proteus mirabilis infections.73 1.1.4 Current available treatments Common treatment options for lower-pole stones (LPS) between 10 to 20mm in size include shockwave lithotripsy (SWL), retrograde intra-renal surgery (RIRS), or percutaneous nephrolithotomy (PCNL). During SWL high-energy shock waves are emitted to break stones so the fragments may be passed. While it is minimally invasive and has a good patient tolerance, unfortunately, not all stones can be fragmented. RIRS has an 82.1% stone free rate for LPS, and PCNL is highly effective (93.8% stone free) but has the disadvantages of being a highly invasive surgical procedure12,13. Despite the success of the current stone removal procedures, recurrence rates after an initial symptomatic stone event range from 30-50% within 10 years of the first occurrence8. A study showed that 81% of interviewed patients would opt to take prophylactic medication than undergo a second stone episode, and 92% preferred medication rather than having to go through another surgery13. Because of the high recurrence rates and the desire to avoid or postpone surgical procedures, metabolic evaluation would benefit the vast majority of stone patients8. This metabolic evaluation consists of a series of exams to quantify the levels of specific urinary components relevant to stone formation. In serum, these include creatinine, sodium, potassium, chloride, calcium, albumin, uric acid, bicarbonate, parathyroid hormone (PTH), and vitamin D. In urine, critical parameters include urine volume and concentration. Substances such as creatinine, calcium, sodium, potassium, oxalate, citrate, uric acid, cystine and magnesium are pertinent to evaluate for crystal formation8. Conservative treatments for both types of hyperoxaluria includes hydration, reducing oxalate rich food intake, and crystallization inhibitors to decrease CaOx precipitation14. The CUA recommends that all stone-formers should achieve a daily urine output of 2.5 L and have a calcium intake of 1000-2000 8 mg/day. For CaOx patients, calcium supplementation should be taken at mealtimes, and if they have deficiency in vitamin D, repletion is recommended, but follow-up monitoring for hypercalciuria is suggested as excess Vitamin D is linked to increased calcium absorption8. In patients with recurrent CaOx and uric acid nephrolithiasis, moderation of animal protein intake and avoiding purine rich foods is recommended. Recurrent calcium nephrolithiasis should aim for 1500 mg of sodium intake and should not exceed 2300 mg. For kidney stone patients, diets high in fibre, fruits and vegetables may offer a small protective effect against stone formation. Vitamin C supplementation of more than 1000mg daily is not recommended due to the risk of hyperoxaluria. Alkali citrates are effective in increasing urinary citrate, urinary pH, and reducing stone recurrence in calcium stone formers8. Since the discovery of Oxalobacter formigenes, an oxalate degrading bacterial species, research looking at the potential role and use of bacteria to prevent and treat KSD has begun. Studies evaluating the use of Oxalobacter as a probiotic to reduce stone formation revealed encouraging but not definitive results. Data shows different colonization rates for stone patients versus healthy controls, but not consistently to all cohorts. One study showed that oxalate degrading bacteria lead to a 70% reduction in the risk for being a recurrent CaOx stone former15. While the administration of Oxalobacter, as a probiotic, did show increased degradation levels of oxalate in the intestine but this effect was not long lasting but rather it was transient.15 1.1.5 Dietary factors that modify kidney stone risk Kidney stone disease originates from metabolic imbalances where concentrations of oxalate, calcium, and various salts are increased in the blood and urine beyond their normal physiological levels2,16. Traditionally, nephrolithiasis has been considered a renal disorder, but increasing evidence indicates that in fact it is a systemic disorder3. 9 The disease can be caused by genetic defects related to endogenous production of oxalate in the liver, and by consumption of high oxalate foods1. Although calcium stones can form as a result of genetically inherited diseases, these correspond to less than 10-15% of calcium stones in the general population3. Thus, most of the calcium stones originate as a result of conditions such as hypercalciuria, hyperoxaluria, and hypocitraturia without a known etiology19. Minerals have a foundational role on the crystal formation process. Sodium intake in healthy adults increases urinary pH, brushite, monosodium urate, and reduces citrate and serum bicarbonate concentrations. Citrate is an important inhibitor of crystallization so its reduction in the urine is a urolithiasis risk factor1. Potassium rich foods including fruits and vegetables play a role in stone formation as their consumption increases renal tubular phosphate absorption which inhibits the syntheses of 1,25-dihydroxyvitamin, resulting in less calcium absorption by the intestines thereby reducing calcium in the urinary system3,8. Diet also plays a critical role in increasing the risk for crystal formation, as foods rich in oxalate increase its bioavailability in the intestines, tending to augment the ratio of transported oxalate to the bloodstream and therefore, to the kidney17. Oxalate absorption and excretion occurs via ion transporters located on intestinal epithelial cells with the direction of oxalate movement being dependent on the pH, section of the intestine, and its concentration on intestinal serosa20,21. The fraction of dietary oxalate that will effectively be absorbed by the intestine is highly influenced by the amount of oxalate binding cations, such as calcium and magnesium, in the gut. Those minerals form insoluble oxalate complexes decreasing oxalate absorption24. For example, a previous study demonstrated an increasing risk for urolithiasis with decreasing calcium intake from 1,050 mg/day to 600 mg/day. The increased risk for stone formation is due to less calcium being available to bind oxalate and form calcium oxalate complexes within the intestine that are then eliminated via the feces1. Instead, the free oxalate is absorbed into circulation. It was shown in previous research that oxalate/calcium molar ratio should be around 1:10 to prevent 10 crystallization, and that changes in oxalate concentration is more likely to initiate crystal formation than alteration in calcium25. Animal protein ingestion is closely associated with the prevalence of stone disease. In Saudi Arabia, the higher prevalence of urolithiasis relates to the high intake of animal protein, determined to be 10% and 50% higher compared to the USA and Europe, respectively10. Similarly, in Japan, prevalence of bladder and kidney stones was the same in 1950, while in 1980 the prevalence of upper tract stones rose to 95%, which coincided with an increase in protein from animal sources from 20 to 40g per day3. In the case of uric acid stones, an increase in uric acid excretion can be related to the consumption of proteins high in purine, which also plays a role in calcium stone formation3. Regular consumption of diets high in processed fats and sugar increase stone risk via a different mechanism. In this case, these foods increase the level of inflammation in the gut causing ion exchange imbalances and the disruption of intestinal epithelial cell tight junctions, leading to a physiologic environment favourable to hyperoxaluria3 due to increased oxalate absorption. Lastly, drugs can also induce stone formation; lithogenic drugs such as triamterene may induce the formation of calculi by its interference with calcium oxalate or purine metabolisms1. Also, it was recently shown that antibiotics can increase stone formation, especially when the system is at a hyperoxaluria state, being a risk factor for crystal formation23. Prior reports indicates that there is a persistent reduction of gut microbiota months after antibiotic exposure, leading to an alteration on the composition of the microbiome and subsequently of macronutrients metabolism. Also, it is possible that antibiotics select for multi drug resistant bacteria in the urinary microbiome responsible to stimulate urolithiasis. This conclusion came after analyzing bacterial strains obtained from calcium stones, where 70% of the isolates were resistant to diverse antibiotics78. 11 1.1.6 Hyperoxaluria and the role for intestinal bacteria in kidney stone formation Oxalate is an anion (C2O4)2- with double negative charge, it can form different type of salts, and it is the conjugated base of oxalic acid (C2H2O4.(H2O)n). Calcium stones are found in the majority of kidney stones (80%), they are composed by calcium oxalate (CaC2O4.(H2O)n) and calcium phosphate (Ca(H2PO4)2.(H2O)n) at different compositions rate2. Hyperoxaluria means high oxalate concentrations in urine, and more than 45mg/day is considered clinical hyperoxaluria. It is a condition of altered metabolism, and it can be classified as primary and secondary hyperoxaluria. The primary hyperoxaluria mostly results from inherited hepatic enzyme deficiencies causing elevated endogenous oxalate synthesis. The secondary hyperoxaluria originates from conditions that will increase intestinal oxalate absorption such as high-oxalate diet, fat malabsorption (enteric hyperoxaluria), alterations in oxalate-degrading and butyrate-producing microorganisms, genetic variations of intestinal oxalate transporters, or deregulated immune responses leading to intestinal inflammation. Other factors such as IBD, diabetes, obesity, and hyperparathyroidism are also known to escalate oxalate absorption in the gut increasing the risk for CaOx crystal formation14,17,18. The physiology of mammals is highly dependent on the metabolic relationship that exists between the host and its microbiota. Microorganisms have 100 times more genes than the host itself 76 and are able to produce a vast number of metabolites that impact metabolic and gut health. It is known that the use of antibiotics and certain diets can alter the host-microbe metabolic network, leading to disease23. Recent research indicates that antibiotic exposure is related to increased nephrolithiasis prevalence, suggesting that the gut microbiota is connected with calcium oxalate stone formation37. One of the fundamental roles of the intestinal microbiome is that they undertake functions that we as their host cannot. Specifically, the host lacks enzymes, which gut microbes have, that perform specific metabolic functions and/or break down compounds that are toxic to our bodies. Many vegetables 12 commonly consumed carry secondary compounds known to be toxic to our tissues if allowed to build up. Several bacteria isolated from the gut can degrade toxic compounds into non-toxic products. Oxalate is a toxic compound, and it can be lethal if taken in high doses leading to hypocalcemia, azotemia, internal hemorrhage and crystal formation in the kidneys18. Oxalate can enter the host due to consumption of common foods such as chocolate, rhubarb, spinach, beets, tea and coffee, and it is also indirectly derived as a terminal metabolite from dietary precursors such as glyoxalate, glycine, ascorbic acid and hydroxyproline in the liver. Despite its regular consumption, the human body lacks the enzymatic machinery to degrade this potentially toxic compound. However, our gut microbiota contains several bacterial species that express specialized enzymes capable of degrading oxalate into formic acid and carbon dioxide65. This is a key mechanism in regulating intestinal oxalate concentrations and subsequent absorption, as its intestinal degradation prevents it from being absorbed into the bloodstream, reducing the risk for hyperoxaluria. The first bacterial species known to degrade oxalate was Oxalobacter formigenes, initially isolated from sheep in 1980 but found later in rats, pigs and humans. It is a strict anaerobic, gram-negative bacteria, that has evolved to mainly utilize oxalate as an energy source via the activity of two intracellular enzymes: oxyl-CoA decarboxylase and formyl-CoA transferase38. Interestingly, O.formigenes was found to be a main oxalate degrader in the foregut of Neotoma albigula, a wild rat capable of consuming significantly higher amounts of oxalate than what would be considered toxic to humans. Its specialization as an oxalate degrader is evidenced by the fact that O.formigenes represents only 0.02% of the total colon bacterial content, whereas other common species, such as Lactobacillus, make up as much as 13%20. While O.formigenes is believed to be a main oxalate degrading species in the intestine, other bacterial species capable of degrading oxalate have been identified, including species from the genera Enterococcus, Lactobacillus, Eubacterium, Bifidobacterium, Eggerthella, Providencia, Streptococcus 13 and Leuconostoc20. More recently, a novel oxalate-degrading member of the Enterobacteriaceae family (Providentia rettgeri)65 was identified in human fecal samples and, notably, this organism also was reported to have enzymes similar to those of O.formigenes. Interestingly, the purpose for degrading oxalate appears to be different between species, with some degrading it as an energy source while others degrade it to detoxify the surrounding cellular environment38. This explains that while these species have the capabilities to degrade oxalate, they do not preferentially do so and only degrade oxalate as needed. Environmental pH is a key element in oxalate degradation. Lactobacillus acidophilus performs optimal oxalatre degradation between pH 4.5 to 5.5, while O.formigenes show maximal activity at pH 6.4. This suggests that intestines have multiple environmental niches, each with differing oxygen levels and different pH ranges resulting in different species degrading oxalate in varying environments along the intestinal tract rather than in just one location. The overall structure of the intestinal tract is an important determinant for the gut microbiota’s ability to degrade toxic compounds such as oxalate. For example, the gut of ruminants is ideal for optimal oxalate breakdown as the microbiota is exposed to a constant concentration of the substance with uniform mixing, whereas in the human gut the exposure is temporal and spatially segregated reducing the effectiveness of the microbiota to break down oxalate20. Bacteria respond distinctively to oxalate concentrations, with some genes becoming up-regulated, while others are down-regulated depending on the amount of oxalate in the surrounding environment. Miller et al 2013, proposed that there are four groups of microbial communities in the gut, one that is positively affected by oxalate because it’s uses as an energy source, a second that is inhibited by oxalate but can break it down for detoxification purposes, a third that is negatively affected but benefits from the oxalate degrading communities, and a fourth that is not affected by oxalate concentrations20. Similarly, Sahin et al 2003 proposed that there are two groups of oxalate degrading bacteria, generalists and specialists. The first group can ferment many other substrates other than oxalate, while the second group use only oxalate as a source of carbon and energy39. 14 The majority of oxalotrophic (oxalate degraders) bacteria are aerobic, gram-negative rods, lithotrophs or facultative methylotrophs, meaning that they can use inorganic compounds such as hydrogen and carbon monoxide as electron donors. Phylogenetic analysis shows that the oxalotrophic bacteria are distributed in the gram-negative, alpha, beta and gamma Proteobacteria phyla, and the gram-positive bacteria belong to the Firmicutes and Actinobacteria phyla39. Previous research showed that bacteria enriched in non-stone formers have a positive correlation with O.formigenes and with other bacteria enriched in rodents capable of degrading significant amounts of oxalate in their gut. Interestingly, having a similar gut microbiota profile to Neotoma albigula (i.e., Oscillospira and Ruminococcus) was more reliable at differentiating stone-formers from non-stone formers than the absence or presence of O.formigenes alone18. This suggests that the maintenance of a healthy oxalate homeostasis in non-stone formers is dependent on the symbiotic interaction of multiple bacterial species and not just the presence of O.formigenes, as what was previously believed. This opens the door for the possibility that metabolic pathways other than oxalate degradation may play a role in recurrent kidney stone disease. In a study comparing the gut microbiota of kidney stone patients and healthy controls, metabolic pathways involved in antimicrobial drug resistance, xenobiotics degradation, and glycan biosynthesis were different between patients and controls. These findings support previous results indicating that antibiotic use is a risk factor for KSD and previous research also suggests that glycan biosynthesis may have a role in hyperoxaluria and KSD18. In the same study, oxalate metabolism between patients and controls was accessed and, surprisingly, no significant differences in the presence of known genes for oxalate degradation pathways were found. This suggests that the overall capacity of the microbiota to degrade oxalate is not different between patients and controls, further suggesting that other mechanisms must be at play40. Along those lines, the study found that a lower abundance of bacterial genes encoding enzymes 15 related to butyrate biosynthesis were found in kidney stone patients suggesting that the gut microbiota of kidney stone formers may have a lower capacity to produce butyrate. In terms of the number of genes that differed between patient and control samples, approximately 62% of genes were related to the butyrate pathway, 47% to glyoxylate pathway, and 36% of genes to ascorbate pathway.18 Using metagenome assembled genome (MAG) techniques recent research shows that the genes more enriched in the control group were affiliated with Faecalibacterium prausnitzii; Clostridiales spp, and Oscillibacter spp. For patients, genes affiliated with Alistipes finegoldii were more enriched18. Additionally, genes associated with butyrate production were affiliated with F.prausnitzii, Alistipes spp and Akkermansia muciniphila18. Collectively, these data support the hypothesis that a lower ability of the gut microbiota to produce butyrate, may play a role in increasing the risk for recurrent kidney stone disease. This was supported by other studies showing 2.3x lower butyrate concentrations in KSD patients44, and a lower abundance of the bacterial gene encoding butryl-CoA in recurrent kidney stone formers aged from 4 to 18 years old.44 1.1.7 Intestinal absorption of oxalate and butyrate producer microbiota The importance of the gut in KSD is highlighted by the fact that it is the site where oxalate derived from food as well as from endogenous sources is absorbed, excreted, and metabolized. In some pathological conditions such as renal failure, considerable intestinal excretion of oxalate occurs, indicating that the gut is an important secondary route for oxalate excretion.21 Oxalate can be absorbed from the intestinal mucosa (lumen) to serosa (gut outer epithelium) through two pathways: paracellular and trans-cellular. The first pathway is dependent on electrochemical potential differences of cations and anions such as oxalate. Intestinal sections have different levels of passive oxalate transport. More proximal sections of the gut, where junctional resistance is normally low and luminal oxalate activity is presumably higher, oxalate is readily absorbed. The opposite happens in 16 distal sections of the colon where luminal oxalate might be lower and tight junction resistance higher21. The relevance of the paracellular via trans-cellular pathway is best observed in the pathological conditions of enteric hyperoxaluria caused by the reduced absorption of fatty acids and bile salts31. Fat malabsorption occurs when both dihydroxy bile acids and fatty acids increase the permeability of the intestinal mucosa to oxalate, and also by the complexion of fatty acids with calcium present in the lumen increases the amount of soluble oxalate that is available for absorption as insoluble CaOx complexes are no longer formed25. Oxalate degrading bacteria and SCFA producers play an important role in keeping oxalate homeostasis and may play a potential role as probiotics in ameliorating fat malabsorption syndrome28. Using short-circuited tissue preparations from rabbits to study trans-cellular transport under controlled conditions, the absorption of oxalate was found to be different between different sections of the intestine. The small intestines and proximal colon showed oxalate net secretion, while the distal colon exhibited net absorption. This can be related to the kind of transport pathway, being predominantly paracellular on the small intestines and trans cellular on the large intestines20,21. The overall process of oxalate transport via absorption and secretion is mediated by anion transporters, more specifically members of the SLC26 gene family, primary located in the small and large intestines21. The overall process involves oxalate absorption on the apical side and efflux on the basolateral side and involves distinct transporters. Studies have shown that SLC26A6 gene represents a major apical membrane pathway mediating oxalate efflux rather than influx in normal conditions.29 Furthermore, a gene disruption study using the Sat1 gene (SLC26A1) localized on the basolateral membrane of intestinal cells, showed that loss of Sat1 expression lead to urinary stone formation and hepatotoxicity67,68. Also, previous studies indicate that oxalate absorption in mouse intestine is mediated by DRA (SLC26A3), its deletion decreased urinary oxalate66,67. Recent research indicates that SCFAs (acetate and propionate) produced by bacteria could reduce urinary oxalate and renal CaOx stones 17 through the upregulation of the oxalate transporter SLC26A6 in the intestine44, which sets precedent for the fact that SCFAs play a role in regulating oxalate absorption. 1.1.8 Short-chain fatty acid production Gut microbiota encompass trillions of commensal bacteria dominated by nearly 1,000 species74. The microbiota in the large intestines is more abundant than in small intestines, and the mucus in this portion of the gut is thicker than the in small intestine. One remarkable group of bacteria are the fermenters of long-chain polysaccharides, such as inulin, which are metabolically turned into SCFAs. This metabolic product is a carboxylic acid with aliphatic tails of one to six carbons with the most commonly produced SCFAs being acetate (C2), propionate (C3), and butyrate (C4)68. SCFAs produced by members of the intestinal microbiota have been shown to play an important role in kidney disease through the gut-kidney axis by regulating inflammation, oxidative stress, and fibrosis26. From the intestinal lumen SCFAs are absorbed into the circulation system through which they gain access to the kidney where they can directly impact inflammatory and fibrotic processes in kidney disease. Of particular relevance to this thesis, a previous study confirmed that SCFAs play a role in reducing calcium oxalate stones in rat models37. Butyrate, a type of SCFA, is the major energy source for colonocytes and fundamental to the maintenance of colonic epithelial health, including epithelial cell integrity via tight junction protein expression. Intestinal tight junction assembly restricts para-cellular ion transport across the intestinal epithelium, a transport mechanism attributed to significant amount of oxalate absorption. Similarly, butyrate is also involved in the regulation of trans epithelial electrical resistance (TEER)37, which is a measure of the electrical resistance across the epithelium and a determinant of the permeability of the intestinal epithelium. In this context, butyrate affects another factor that has an impact on oxalate absorption in the intestine. 18 1.2 Rationale for thesis project Recent studies have shown a role for members of the intestinal microbiome in recurrent kidney stone disease, as microbiome composition of recurrent kidney stone formers has been shown to be different from that of non-stone forming individuals. While early research has focused on a single bacterial species, O.formigenes, recent studies by our group and others have shown that O.formigenes does not act alone but rather it acts within a bacterial network. That said, our studies18 as well as others have also found no difference in the overall capacity of the intestinal microbiome of patients and controls to degrade oxalate, suggesting that mechanisms other than oxalate metabolism may play a role in increasing the risk for recurrent kidney stone disease. Based on our most recent studies, we have proposed that increased risk for stone formation may be associated with a decreased capacity of the intestinal microbiome to produce butyrate. This was also supported by results from other studies37. Given the role of butyrate in regulating tight junction proteins and TEER, two key determinants of intestinal permeability and the absorption of compounds, including oxalate, as well as the role butyrate plays in altering the expression of known oxalate transporters, studying the impact butyrate has on regulating oxalate absorption in the intestine is warranted. The purpose of this MSc thesis was to expand this initial work and investigate the impact of increasing butyrate production on oxalate absorption using a diet-induced mouse model of hyperoxaluria. There are two ways in which butyrate production by members of the intestinal microbiome can be increased. The first involves utilizing a prebiotic supplement which leads to the expansion of SCFA producers46. The second involves using a synthetic SCFA that when given in higher amounts will lead to increased SCFA concentrations. Specifically pertaining to butyrate production, inulin is a soluble fibre known to increase the growth of butyrate-producing bacterial species as it acts as the main substrate for bacterial fermentation46. Inulin is a polysaccharide present in various foods such as artichoke, garlic, chicory root. It is not digested 19 in the intestine as humans don’t produce the correct enzymes and therefore relies on bacterial enzymes to degrade it. Tributyrin on the other hand is a triglyceride consisting of three molecules of butyric acid and a glycerol backbone which can act as a precursor for increased butyrate concentrations 47. Inulin does so by increasing the number of bacterial species that produce butyrate, while tributyrin breakdown by the fatty acid-metabolizing bacterial species75, results in increased levels of butyrate. The overall objective of this thesis was to develop a diet-induced hyperoxaluria model in mice and assess the effect of high oxalate +/- supplementation with inulin and tributyrin on intestinal microbiome composition, as well as urine oxalate concentrations in mice. This work lays the groundwork for future studies assessing the impact of increasing the availability of butyrate on oxalate absorption. Hypotheses and aims Hypotheses: a) We hypothesize that elevated oxalate concentrations in the gut (enteric hyperoxaluria) results in the development of hyperoxaluria, causes the reduction of microbial diversity and impacts the production of SCFA. High oxalate levels in the gut could potentially alter the gut microbiota, leading to species loss, and therefore reduction of important genes related to gut homeostasis and oxalate metabolism. b) We also hypothesize that inulin (prebiotic fibre) and tributyrin (source of butyrate) supplementation will increase the abundance of species known to produce butyrate as well as the amount of butyrate in the intestine. Aims: Aim 1: Develop a diet-based model of hyperoxaluria in mice. Assess the impact of high oxalate levels on intestinal microbiota diversity and composition and in urine oxalate levels . Determine if hyperoxaluria induced by diet will cause crystal formation on kidney tissue. Aim 2: Develop diet-based model to study the impact inulin and tributyrin supplementation has on gut microbiota diversity, composition, and SCFA concentrations in stool and cecum content. 20 Figure 1: Scheme representation of extracellular events during nephrolithiasis. Taken from Aggarwal et al, 2013. 21 2 Materials and Methods 2.1 In vivo model All animal procedures describe herein were approved by the University of British Columbia Animal Care Committee under protocol A18-0356. C57BL/6 mice were fed conventional mouse chow supplemented with pertinent additives. To test our hypothesis, we performed two distinct experimental approaches. The first one contained two diets administrated to the mice, high oxalate and control diet, the second one contained four diets given to the mice, high oxalate, control, inulin, and tributyrin. The conventional chow given routinely to laboratory mice (Teklad Global Soy Protein-Free Extruded Rodent Diet- 2020X) have the standard mineral composition of 0.9% Ca, 0.7% Phosphorus, and 0.1% sodium. To study the effects of sodium oxalate, inulin and tributyrin on the gut microbiota customized Teklad diets were ordered from Envigo. In total, four different diets were used: 1) Control chow containing 0.5% calcium, 0.4% phosphorous and 0.5% sodium 2) Chow supplemented with 1.5% sodium oxalate, 0.5% calcium and 0.4% phosphorous 3) Chow supplemented with 1.5% tributyrin, 0.5% calcium, 0.4% phosphorous and 0.5% sodium 4) Chow supplemented with 10% inulin, 0.5% calcium, 0.4% phosphorous and 0.5% sodium To study how increasing butyrate levels via the endogenous route affects the gut microbiota mice were fed chow supplemented with 10% inulin, a prebiotic fibre that is metabolized into butyrate by gut microbes68. To study how increasing butyrate levels impact the microbiota via exogenous routes, we supplemented chow with 1.5% tributyrin, a butyrate precursor. Lastly, to analyze the effects of high oxalate levels on the gut microbiota, 1.5% of sodium oxalate was added to the control chow diet. All four customized diets were developed in consultation with a Envigo nutritionists. Other than the differences in nutrients stated above all four diets had very similar protein, fat, carbohydrate and micronutrient content (Table 1). 22 Table 1: Nutritional composition of the Envigo formulated diets Formula components / Diets (g/Kg) Control Oxalate Inulin TributyrinCasein 200 200 200 200DL-Methionine 3 3 3 3Sucrose 340.42 340.01 340.42 340.42Corn Starch 250 250 250 250Cellulose 100 100 N/A 100Corn Oil 50 50 50 35Mineral Mix, Ca-P Deficient (79055) 13.37 N/A 13.37 13.37Calcium Phosphate, dibasic 11.5 11.5 11.5 11.5Calcium Carbonate 4 4 4 4Sodium Chloride 10.5 N/A 10.5 10.5Vitamin Mix, AIN-76A (40077) 15 15 15 15Chlorine Bitartrate 2.2 2.2 2.2 2.2Ethoxyquin, antioxidant 0.01 0.01 0.01 0.01Potassium Chloride N/A 3.3 N/A N/APotassium Citrate, monohydrate N/A 2.9 N/A N/APotassium Sulfate N/A 1.8201 N/A N/AMagnesium Oxide N/A 0.084 N/A N/AManganous Carbonate N/A 0.1225 N/A N/AFerric Citrate N/A 0.21 N/A N/AZinc Carbonate N/A 0.056 N/A N/ACupric carbonate N/A 0.0105 N/A N/APotassium Iodate N/A 0.0004 N/A N/ASodium Selenite, pentahydrate N/A 0.0004 N/A N/AChromium Potassium Sulfate, dodecahydrate N/A 0.0193 N/A N/ASodium Oxalate, customer supplied N/A 15 N/A N/AInulin N/A N/A 100 N/ATributyrin, customer supplied N/A N/A N/A 15Selected nutrient information Control Oxalate Inulin Tributyrin% by weight / % kcal fromProtein 17.7 / 20.2 17.7 / 20.3 17.7 / 19.6 17.7 / 20.2Carbohydrate 58 / 66.4 58 / 66.4 61 / 67.5 58 / 66.4Fat 5.2 / 13.4 5.2 / 13.4 5.2 / 12.9 5.2 / 13.4Kcal/g 3.5 3.5 3.6 3.5 For each experiment, twenty-five 9-week-old C57BL/6 male mice were ordered from Charles River. Mice were co-housed with each other to help normalize the gut microbiota composition prior to splitting them into each dietary group. This co-housing was approved under the animal care protocol. The mice were co-housed for 3 weeks prior to initiating the diets. For the first week the mice were on the normal facility chow (Teklad 2020) (pre-treatment) then they were commenced on the control diet for 2 weeks (acclimatization). After acclimatization the mice were divided in to the four dietary groups 23 and fed on these diets for 2 weeks (Table 1) as follows: Group 1: Mice on control diet – 2 weeks Group 2: Mice on sodium oxalate diet – 2 weeks Group 3: Mice on inulin diet – 2 weeks Group 4: Mice on tributyrin diet – 2 weeks Table 2: Experimental diet plan mice were on over 5 weeks Phase Duration Diet No. of miceAcclimatization 1 week Facility chow 25Pre-treatment 2 weeks Control chow 25Treatment 2 weeks Control chow 6Inulin chow 6Tributyrin chow 6Sodium Oxalate chow 7 During the 5 weeks of the experiment, mice were weighed and food and water consumption was measured at least once a week. Stool, urine and blood samples were collected prior to the treatment phase, one week in to the treatment period and at the end of the study immediately following euthanasia (Table 3) which was performed via isoflurene followed by cardiac puncture. Urine was collected using a small container containing hydrophobic sand (LabSand manufactured by Coastline Global US), which is nontoxic, sterile and biodegradable. Deposited urine formed a drop on the sand and was collected via a sterile pipette tip. This collection method was chosen as it is less stressful for the animals than using metabolic cages which requires the animals to be kept in the metabolic cages for an extended periods of time. Urine was collected 4 times a day during the three collection dates to ensure that the collected sample was representative of a 24hr period. Stool was collected at the same 24 time, making sure that none of the fecal pellets came in contact with the urine sample. Stool samples were also collected at the same time points that urine was collected. Blood (100 uL) was collected via tail vein poke according to an approved SOP (SOP ACC-2014-Tech12 - collection of small amounts of blood from tail tip micro sampling in mice) and then transferred to a thin capillarity tube to be further centrifuged to separate plasma. At experimental endpoint, blood was collected using a cardiac puncture (1.5 to 2mL). All samples were kept on ice during collection and then transferred to a -80 °C freezer. Kidneys, cecum and colon were harvested. Representative fragments from each tissue were immediately preserved in 10% formalin for histology, in RNAlater for transcriptomic analyses and flash frozen for DNA analyzes. Table 3: Sample collection plan Experiment Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35Diet Facility chowBase chowExp. ChowMicrobiota synch MSSample collection Blood Stool UrineCecal contentOrgans 25 2.2 Analytical chemistry High performance liquid chromatography was chosen due its high accuracy and reliability for low analyte concentrations in each sample. HPLC/MS oxalate measurements Prior to beginning the process, stool was weighed, re-suspended in 0.1 % formic acid (FA) and centrifuged for 2 min at 20,000 xg (Centrifuge 5424 R Eppendorf Acme) with the supernatant collected for analysis. Aliquots of urine, plasma and extracted stool were combined with carbon-13 labelled oxalate plus 2% formic acid solutions, and centrifuged for 2min at 20,000 xg. The supernatant was inserted in an ultra-filtration filter (Amicon® Ultra 0.5mL 10K centrifugal filters) and centrifuged at 12,000 xg for 15min. The filtrate (samples) was then loaded into a SPE cartridge (Oasis® Wax 3cc cartridge 60mg 30µm), preconditioned with a run of methanol followed by Milli Q water. Following addition of the samples, two washes were performed using 2% FA followed by methanol. The samples were then eluted with a 5% ammonia solution in methanol. The eluted solution was then loaded into Centrivap® (Centrifugal Vacuum Concentrator, Labconco) for about 30 minutes to be dried completely. The precipitate was then re-suspended in 0.1% FA, and centrifuged for 2min at 20,000 xg. The supernatant was collected and processed by HPLC/MS. The filtration process removes the larger organic molecules and cellular debris, and the SPE remove salts as well as retains and releases strong acids. The LC columns employed to assess the analytes were a 2mm x 150mm 5µm C18 PAQ Cosmosil Nacalai Tesque that had longer oxalate retention than the Waters 2.1mm x 100mm BEH Shield C18 where oxalate came out of the column earlier. A carbon thirteen labelled oxalate was utilized as an internal standard. A total of 50 urine, 25 stool, and 25 blood samples were analyzed. 26 Short-chain fatty acid analysis A total of 66 mouse cecal samples were submitted for SCFA analysis. A 30 uL aliquot of supernatant was mixed with 50 uL 2-Butanol/Pyridine (3:2) containing the`. The carboxylic acids were then derivatized with isobutyl chloroformate. After derivatization, the sample was mixed with Hexane and the hexane layer was removed for GC-MS analysis. The quantitation of acetic acid, butyric acid, isovaleric acid, lactic acid, propionic acid, and succinic acid was performed using isotope dilution GC-MS/MS. The absolute quantity of each SCFA was determined using calibration curves measured for each analyte. For the longitudinal change in SCFA profiles, the starting SCFA concentration was subtracted from the final for each animal, resulting in the overall change in SCFA concentrations. For the differences in SCFA profiles, the values were taken from the cecal samples for a direct group comparison. 2.3 Molecular biology methods Bacterial DNA extracted from mice stool samples was amplified and sequenced to evaluate microbiota abundance and diversity within the samples before and after diet treatments. Diverse operational taxonomic units (OTUs) and higher taxonomic categories were established, and a correlation with oxalate and butyrate bacterial networks related with diet intake were established. DNA extraction and Next Generation Sequencing DNA was extracted from 20mg of stool pellets or cecal contents using the semi-automated KingFisher Duo Prime machine (ThermoFisher) using the protocol for stool. Resulting DNA concentration was quantified on a Qubit Fluorometric quantification. Library prep for 16S sequencing was conducted through amplification of the V4 region of the 16S gene (primers 515F and 806R). Amplification was done using the Nextera XT library preparation kit 27 (Illumina). Amplicons were quantified and quality controlled with Qubit Fluorometric quantification and pooled prior to sequencing. Negative controls included DNA extraction reagents, sterile water, and negative PCR samples were used. Sequencing was performed as paired, 151 base pair sequences on an Illumina iSeq. Statistical analysis Regarding the treatment and analysis of the data generated by the sequencing, the following techniques and parameters were used. Taxonomic assignment in Dada2 to amplicon sequence variants was based on a combination of the Silva and NCBI 16s gene databases. Decontaminated against negative controls was undertaken using Decontam and samples were normalized using DESeq2. Alpha diversity using phylogenetic diversity, ANOVA and pairwise t-tests and beta diversity using weighted unifrac analysis, PERMANOVA and pairwise PERMANOVA were undertaken. Differential abundance using FDR-corrected DESeq2 was performed. The longitudinal data (between two time points) was calculated by comparing the starting alpha diversity (two weeks after consuming base chow) to the final alpha diversity (two weeks after consuming treatment diets) for each animal, resulting in the overall change in alpha diversity. For beta diversity, absolute change in unifrac distance for each animal was calculated, resulting in change in microbiome composition. For the microbial differences on diversity observed on cecal content, samples represent the microbiota at the endpoint of the experiment. In that case, we have data collected only once as mice needed to be euthanized to collect this sample type. 28 2.4 Histological methods For histology analysis of the kidneys before and after the diet treatments, H&E staining was employed to identify any pathological alteration of the kidney cortex and occurrence of mineral aggregates and oxalate crystals. Kidneys were collected at the endpoint of the experiment and fixed in 10% formalin solution after being harvested. Once fixed, a longitudinal section was cut to expose the cortex, producing two tissue samples per kidney. Tissue samples were dehydrated using sequential incubation in 70%, 80%, and 90% ethanol solution for 1h each, and two changes of 100% ethanol solution for 1h each. Finally, two changes of xylene for 1.5 hrs each, and after this, dehydrated tissues were embedded in paraffin using plastic cassettes. Cassette surfaces were cooled with ice to improve cut efficiency. The microtome was adjusted for 5µm cuts. Thin cuts of tissue were placed into a water bath (40 Celsius) for a few minutes to unfold. After baking the slides for 60 min at 58C, they were deparaffinized and rehydrated by immersing them in a 100%, 95%, 90%, 80%, and 70% ethanol solution for 2-5 min each. At this point, the tissue slides were ready for staining accordingly with Hematoxylin and Eosin stain (H&E) using a protocol from the Center for Musculoskeletal Research of the University of Rochester Medical Center. In brief, slides were stained in Mayers Hematoxylin for 1 minute, washed with 4-5 changes of tap water or until blue dye stopped running off the slides and blue nuclei were visible. The sldies were then placed in 1xPBS for 1 minute and washed with three changes of distilled water. Counterstaining took place in alcoholic-eosin for 1 minute, followed by dehydration via three changes of 95% EtOH and two changes of 100% EtOH for 1 minute each. The slides were then cleared using three changes of Xylene for 1 minute each, mounted and a coverslip was applied. 29 3 Results 3.1 Impact of diet on urinary oxalate levels Figure 2: Oxalate levels in mouse urine after consuming the control, sodium oxalate, inulin and tributyrin diets before (blue) and after (orange) the treatments. Results show that there was a trend towards higher urine oxalate levels in mice treated with high oxalate diet compared with controls 1,013 mM versus 623 mM, respectively p = 0.4271 ), and urine oxalate levels were lower in the urine of mice treated with inulin comparing with controls 238 mM versus 623mM, respectively p = 0.0429). Urine oxalate levels in tributyrin treated mice were similar to the control group 494 mM versus 623 mM, respectively p=0.8203). These results also demonstrated that the oxalate levels across groups at baseline were similar, as expected. Additionally, the post intervention oxalate levels were the highest in the oxalate treated group, confirming that this diet can cause hyperoxaluria. Although these differences are not significant there is a trend towards the high oxalate 30 diet leading to higher urine oxalate levels and the inulin diet, which promotes SCFA production, leading to lower oxalate levels. Additional data points would have likely lead to significant differences between groups. 3.2 Impact of high oxalate diet on intestinal microbiome composition Figure 3: Alpha diversity shift in mouse stool microbiota after consuming the control (Control T1, Control T2, Treated T1) and sodium oxalate diets (Treated T2) between time point one (T1) and time point two (T2). Initially, we compared the control and high oxalate diets. In terms of diversity, we found a significant decrease in microbiota alpha diversity (p-value 0.008) in the stool samples of mice after treatment with the high oxalate diet (Fig. 3). This result support the hypothesis that oxalate reduces microbial diversity. 31 Figure 4: Beta diversity shift in mouse stool microbiota after consuming the control (Control T1, Control T2, Treated T1) and sodium oxalate diets (Treated T2) between time point one (T1) and time point two (T2). We also see significant differences in microbiota beta diversity (p-value - 0.03) of mice treated with high oxalate diet (Fig.4), suggesting that there is a shift in gut microbiota composition after high oxalate diet treatment. This indicates that a distinct gut microbiota community is generated when mice are fed a high oxalate diet. 32 Figure 5: Mice stool microbiota relative abundance differences after control and sodium oxalate diet treatments. Regarding the relative abundance at phylum level we have similar abundance between control groups confirming the validity of the experiment (Fig5). For the high oxalate (treated) group we have no significant phylum level differences, despite of decreasing in the alpha diversity for the high oxalate group. 33 Figure 6 : Mice stool microbiota relative abundance differences at lowest assigned taxonomic distribution level after base chow and sodium oxalate diet treatments. For the lowest assigned taxonomic distribution (the lowest taxonomic hierarchical level sequenced for a specific group of microorganisms), we also did not found significant differences between control groups and high oxalate (treated) groups (Fig.6). That again confirms the validity of our control diet (Fig.7). The microbiome lacked many of the taxa associated with effective oxalate metabolism (Oxalactobacter, Methanobrevibacter, Desulfovibrio and Muribaculum) but did contain some others in low abundance related to oxalate degradation (Lactobacillus, Coprococcus (Lachnospiraceae), Ruminococcus, Bacteroides)36. 34 3.3 Impact of high oxalate, inulin and tributyrin diets on intestinal microbiome composition For the second experimental setup we compared the effect control, high oxalate, inulin, and tributyrin diets had on alpha and beta diversity, and relative abundance of microbial taxa after sequencing the stool of the treated mice. Figure 7: Alpha diversity values of mice stool microbiota after four diet treatments. P value reflects global ANOVA. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. Overall, alpha diversity was significantly reduced in the animals fed the inulin (p value 0.01) and oxalate (p value 0.05) diets compared to animals on the control diet. While mice fed the tributyrin supplemented diet had a similar alpha diversity to control mice (Fig.7). 35 Figure 8: Beta diversity values for stool samples after four diet treatments. P value reflects global ANOVA, * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. In terms of beta diversity, the intestinal microbiome of animals in the control, oxalate and tributyrin groups did not differ significantly (Fig.8). In contrast, inulin supplementation increased the beta diversity significantly, showing that the microbial community in these mice were distinctive from the other dietary treatment groups (p value 0.001). Therefore, both alpha and beta diversity matrices indicate that inulin had the greatest impact on the microbiome, however, oxalate also reduced alpha diversity compared to the control group (Fig.7). 36 Figure 9: Mice stool microbiota relative abundance differences at the phylum level after four diet treatments comparing the start point (base chow) and final point (Control, Inulin, Oxalate, Tributyrin) within the same mice group. When observing phylum relative abundance, we didn't see significant changes in the control, oxalate and tributyrin diets (p>0.05). Conversely, for inulin fed mice we observed a reduction in Firmicutes and Bacterioidetes when compared to high oxalate fed mice (Fig.9), however, these differences weren’t significant . 37 Figure 10: Mice stool microbiota relative abundance differences at the lowest assigned taxon level after control and sodium oxalate diet treatments. For the differential abundance of ASVs, what is shown is the number of amplicon sequence variants that were significantly different between groups. Specific significant difference is based on log2 fold change coupled with standard error (DESeq2 algorithm). Regarding the abundance of ASVs we revealed a significant reduction in Lachnospiraceae and Clostridia group members , both belonging to Firmicutes phylum. We also noticed a loss of members belonging to Oscilospiraceae and Ruminococcaceae in the high oxalate group (Fig.10). 38 Figure 11: Shows differential abundance on mice stool microbiota after consuming base chow (Control) and Inulin at the endpoint for different mice groups treatments. From the ASVs obtained after sequencing the stool, we can observe the presence of many more ASVs in the control group compared with the inulin (Fig.11), confirming the lower alpha diversity for the inulin group (Fig.7). A reduction of the Lachnospiraceae group and an increase in Clostridia is observed for the inulin group. 39 For the second experimental setup, we sequenced the cecal contents of mice on the control, inulin, tributyrin and high oxalate diets, to demonstrate whether there were any differences in relative abundance, ASVs abundance, alpha and beta diversity. Figure 12: Alpha diversity values from cecal content after the four diet treatments. P value reflects global ANOVA, * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. For the cecal microbial alpha diversity, we also found a similar result as with stool samples, with a more significant reduction in diversity in the inulin group (p value 0.001). 40 Figure 13: Beta diversity shift on mice cecal content microbiota after consuming base chow (Control T1, Control T2, Treated T1) and sodium oxalate diet (Treated T2) between time point one and time point two. For the beta diversity of cecal contents (Fig.13) we also found a similar result to what was observed in the stool samples (Fig.8). Specifically, we noticed a significant shift in gut microbiota composition in the inulin treated group (p value 0.001), as well as a significant difference in beta diversity between the high oxalate and control groups (p value 0.004). 41 Figure 14: Mouse cecal content microbiota relative abundance differences at the phylum level after four diet treatments at the final experimental time point. Again, we found similar changes in cecal phylum abundances (Fig.14) as we observed in the stool samples (Fig.9). We observe reductions in Bacteroidetes and Firmicutes for both high oxalate and inulin dietary groups, however, this was more pronounced in the inulin group. 42 Figure 15: Number of ASVs/ Taxon abundance in mouse cecal content microbiota after consuming control and inulin diet Interestingly, the number of ASVs found to be significantly different between control and inulin groups was higher in inulin group (Fig.15) which is the opposite of what was found in stool samples (Fig.11). Specifically, the taxa that were the most abundant in the cecal contents of mice on the inulin diets were Lachnospiraceae and Clostridia which are known SCFA producers. 43 3.4 SCFA profile differences between groups for stool and cecal samples Here, we will discuss the differences in specific SCFAs (acetic, butyric, isovaleric, lactic, propionic, and succinic) concentrations in the stool and cecum of mice treated with control, inulin, tributyrin, and high oxalate diets. Figure 16: Final concentration of acetic acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B). P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. From the changes in acetic acid we can see that the net values (concentration after treatment subtracted from concentration before treatment) have increased, meaning that all diets have promoted acetic acid production. We found significant differences between inulin and the control (p value 0.05), tributyrin (p value 0.05) and high oxalate (p value 0.01) diets. Whereas, for the final concentrations we only see differences between the inulin and high oxalate groups (Fig.16). 44 Figure 17: Final concentration of butyric acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B). P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. For butyric acid, we can observe an increase over time for all the diets, but no significant differences between the groups. Butyric acid is one of the most known SCFAs capable of influencing oxalate absorption in the intestine. It is contradictory that butyric acid is present at similar concentrations in all dietary groups. However, oxalate reduction in the urine of mice on the inulin diet was observed so it’s possible that microbial metabolites might also impact oxalate production. 45 Figure 18: Final concentration of isovaleric acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B). P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. For isovaleric acid, we observe a significant decrease in the high oxalate group. Conversely, the inulin, control and tributyrin groups had a significant increase in isovaleric acid levels. Specifically, we observed significantly greater changes in isovaleric acid levels in the control and inulin groups compared to the oxalate group (p value 0.001) (Fig.18). This indicates that inulin and oxalate treatments are producing divergent results in terms of isovaleric acid as well as overall SCFA production (Fig.18). This supports our hypothesis that stone formers have a reduced diversity of SCFA producers and consequently SCFA concentrations. 46 Figure 19: Final concentration of lactic acid in cecal content samples (A), and change in acetic acid in stool before and after treatment in stool samples (B). P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. For the lactic acid, we observed that inulin fed mice had a significantly greater change compared to the other groups (p value 0.001). Additionally, the other groups experienced minimal changes in their lactic acid concentrations (Fig.19). 47 Figure 20: Final concentration of propionic acid in cecal content samples, and change in acetic acid in stool before and after treatment in stool samples. P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. The inulin group had significantly greater changes in propionic acid concentrations compared to the control (p value 0.05), tributyrin (p value 0.01) and oxalate (p value 0.001) groups (Fig.20). 48 Figure 21: Final concentration of succinic acid in cecal content samples, and change in acetic acid in stool before and after treatment in stool samples. P values calculated using ANOVA test. * reflects pairwise comparisons *p<0.05, **p<0.01, ***p<0.001. Lastly, succinic acid concentrations have similar results to what was observed with lactic acid. Specifically, the inulin diet led to significantly greater changes in succinic acid compared to other groups (p value 0.001) (Fig 21). Additionally, the control, oxalate and tributyrin groups had similarly low succinic acid concentrations. 49 3.4.1 Correlation between SCFA profiles and ASVs Figure 22: Number of ASV's per lowest assigned taxonomy that exhibited a significant, positive correlation between ASV abundance and SCFA concentration for acetic, butyric, isovaleric, lactic, propionic and succinic acids. Figure 22 summarize microbiota sequenced from stool displayed as numbers of ASV's per lowest assigned taxonomy that exhibited a significant, positive correlation between ASV abundance and SCFA concentration. 50 Table 4: Shows the number of ASVs associated with SCFA Table 4 shows the number of ASVs from each taxa that had a positive correlation with a specific SCFA. In total, lactic acid has a total of 48 ASVs related to SCFA production, succinic 46, propionic 24, acetic 22, butyric 16, and isovaleric 15 ASVs correlated. It is valuable to discern that butyric and isovaleric acids that had the lowest ASVs association are the same that had no significant differences between SCFA produced by control and inulin group. In contrast, lactic and succinic acids were the ones where the differences between control and inulin groups were the highest, indicating that the majority of the correlated taxa is deriving from stool sequenced were from the inulin group. 51 3.5 Histology To determine whether the different diets, especially the sodium oxalate diet, resulted in structural changes to the kidneys, we analyzed H&E stained tissue sections from kidneys of animals on the different diets. Interestingly, all kidney sections from animals on the sodium-oxalate diets showed crystalline agglomerates. These were not observed in kidney sections from animals on any of the other diets (Fig.23, Fig.24). Figure 23: Thin sections of the kidney cortex from animals on control and sodium oxalate diets. Arrows indicate crystal location. 52 Figure 24: Thin sections of the kidney cortex from animals on regular control) (K3) and sodium oxalate diets (K24, K25). Arrows indicate crystal location. 3.6 Food and water consumption by animals Measurement of food consumption indicated that animals tended to reduce food intake for the first days after shifting from the control to any of the treatment diets, however, their intake went back to normal after four or less days on the new diet. Interestingly, the high oxalate group had the lowest food consumption overall. Animals on the tributyrin diet had feeding behaviour closest to that of animals on the control diet, while animals on the inulin diet normalized ingestion after the third day on the treatment diet (Fig.25). 53 Control High Oxalate Inulin Tributyrin0510152025Diet Consumption Over Time in Grams per CageD1D2D3D4D5D7D10 Figure 25: Average food consumption (grams) over time for mice on the four different dietary treatments. For the water consumption, animals on the sodium oxalate diet consumed the greatest amount of water, while animals on the tributyrin diet consumed the lowest amount of water. Animals on the control and inulin diets were similar. (Fig.26). Control High Oxalate Inulin Tributyrin0510152025303540Water Consumption Over Time In GramsD2D3D5D8 Figure 26: Average water consumption (grams) over time for mice on the four different dietary treatments. 54 4 Discussion Diet plays a unique and fundamental role in influencing the structure and function of gut microbiota. Toxins present in food, mainly from plants, shape the microbial community which has implications for host health. Oxalate can either benefit or disrupt bacterial species and microbial interactions and has been shown to induce the regulation of over 300 genes45. Overall, results show that a high oxalate diet had a deleterious effect on the mice microorganisms by the reduction of the alpha diversity (15% less diverse when compared to control diet) indicating that when oxalate interacts with poor oxalate-degrading microbiota, such as those in laboratory rodents, diversity drops, urine oxalate levels increase, and crystal formation appeared in kidney tissue. These results are not unexpected as it has been shown in previous studies45 that when the intestinal microbiota is exposed to an unknown toxin there is a loss of microbial diversity. At this initial exposure time point, bacterial communities are not “equipped” to properly metabolize the compound. With continuous exposure to the harmful chemical, some gut microbiota species can be naturally selected as they are able to benefit from it. This has been observed in Neotoma albigula, a rodent with a diet that constitutes mainly of cacti, which are able to degrading 10x more oxalate than humans due to their specialized microbiota capable of degrading oxalate45. A microbiome study of Neotoma albigula45, several bacteria taxa were reported to be positively stimulated by oxalate. In our study showed 7 (Akkermansia, Allobaculum, Bacteroides, Lactobacillus, Oscillospira, Parabacteroides, and Ruminococcaceae) of the 18 taxa identified in the Neotoma albigula45 were observed. The number of taxa stimulated in Neotoma and how responsive they are to oxalate indicates how well adapted it is to this compound. Conversely, in laboratory mice used in our study the majority of these taxa are not present and the ones that are present don’t always appear to respond to oxalate (e.g. ). Comparing microbiota from mice on the control and high oxalate diets we observe a decrease of the Firmicutes taxa and an increase of Proteobacteria and Bacterioidetes (Fig.2). 55 Interestingly, this trend is also observed for Neotoma in an even higher degree, less Firmicutes, more of Bacteroidetes.45 Along these lines, studies comparing microbial diversity between KSD patients and healthy controls observed similar trends regarding the increasing of relative abundance on Bacteroidetes, Proteobacteria, Actinobacteria, and the decrease of Firmicutes and Tenericutes37. For the lowest assigned taxon level (Fig.6), we observed a decrease of important taxa related to oxalate metabolism and SCFA production after the consumption of high oxalate diet. Three important SCFA groups, Lachnospiracea, Oscillospiracea and Oscillospirales, were present in the control group but not present in the high oxalate group (Table 4). Ruminococcaceae (Fig.10) Oscillospirace and Ruminococcaceae are also significant groups responsible for oxalate degradation and the production of succinic acid and acetic acids.(Table 4). RF 39 order, an important taxon related to a positive response to oxalate was reduced in the high oxalate diet group. Furthermore, the high oxalate group had lower amounts of isovaleric acid in their stool compared to control. These results show the same trend observed on recent findings comparing the microbiota of kidney stone formers and non stone formers, where stone formers had lower amounts of butyrate (butyric acid) (SCFA) genes than non stone formers, and in this study, mice fed with inulin also had more SCFA production (succinic, propionic and lactic acids) . All together, this data suggests that even when a host has a particular oxalate-degrading group present in hers/his microbiome, that does not mean that the bacteria associated with it will promptly respond positively to oxalate stimulus. Indicating that a positive response to oxalate depends more on a complex adapted bacterial community rather than by exclusively the presence of specific groups related to its metabolism. These results were also observed in a Neotoma albigula research showing that microbiota interconnection was reduced when the toxin metabolism threshold was reached.45 These data suggests that key taxa related to oxalate metabolism and SCFA production need to be present in the host. However, more importantly, they should be efficiently inter connected to be able to generate a cohesive response to a stimulus. 56 It is interesting to observe how alpha diversity varied for each mice (7 total) in the high oxalate group (Fig.7). One mouse had higher diversity than the average diversity of control group, 2 mice had bacterial diversity within the range of the control group, and four mice had alpha diversity below the range of control group (Fig.7), showing that differences in species richness between these two communities (control x sodium oxalate) are not so expressive for all oxalate treated mice. We also observed that during sodium oxalate diet consumption, two mice presented severe weight lost, four showed moderate loss and one gained weight, showing, clearly, that each individual responded in a particular way despite of all the microbiota synchronization and the fact they all come from the same lineage. These findings could be related to how each mouse was able to establish its own microbial network connections, as it is exemplified in the study of microbiome interactions for Neotoma45. In the mentioned publication, microbial interaction rate increase with the optimal oxalate concentration, and decrease when the optimal threshold value is surpassed, possibly, each mouse had its own tolerance of oxalate based in the complexity of their microbial community interaction. Furthermore, genetic host factors can be also involved in this response, interbreed matting for laboratory mice is useful to produce a homogeneous lineage for research, but also is a source for naturally occurring genetic defects, as gene deletions and insertions. These possible factors responsible for the different responses to oxalate can be further investigated by employing microbial multilayered cooccurrence network analysis of OTU's that exhibit a significant positive Spearman's correlation to oxalate consumption45, and evaluation of gene expression of important gut transporters as the ones belonging to the SLC26A family that could be either deleted or sub-expressed. Overall, the administration of high oxalate diet resulted in an increase in urine oxalate levels as well as the formation of crystals in the renal cortex comparing with the control group after two weeks of treatment. These results confirm previous findings45 were laboratory rodents exposed to 1.5% sodium oxalate presented loss of alpha diversity and increasing oxalate concentrations in the urine. The crystal 57 formation in the kidneys of the sodium oxalate group and its absence in the other groups indicates that oxalate was absorbed in the intestines, crossed the bloodstream and ended up accumulating in kidney tissue. This suggests an inability of the host and microbiota to prevent oxalate absorption in the gut and its subsequent build up in the kidney. We have therefore developed and described a model which can be used to further explore the effects oxalate +/- alterations in diet can have on urine oxalate concentrations and kidney crystal formation. The microbiota composition was significantly altered by the inulin diet, which was characterised by a decrease in alpha diversity, increase in beta diversity, SCFA-producers and SCFA production in the gut. Previous research using inulin as a diet supplement also encountered a reduced alpha diversity for inulin treated group41. In our study, alpha diversity in the inulin group reduced by 35% compared with the control group. On the other hand, beta diversity was significantly increased in the inulin group. In terms of the taxonomic groups altered by the inulin diet compared with the control diet we observed a reduction of Firmicutes members and an increase of Bacteroidetes, Proteobacteria and Verrucomicrobia. Comparing the endpoint concentrations of cecal SCFAs between the control and inulin groups we observed that important taxa related to SCFA production were increased in the inulin group such as Lachnospiraceae and Oscillospiraceae.77 Additionally, an inulin supplemented EEN formula was shown to lead to increases in SCFA producing bacteria such as Bifidobacterium spp. and Anaerostipes caccae.41 Similarily, the high oxalate diet also had an impact on bacterial alpha diversity although less marked than what was observed in the inulin group. Conversely, the high oxalate diet did not altered beta diversity or increased SCFA production and the tributyrin diet didn't promote significant alterations in alpha and beta diversity or altered overall SCFA production. These results clearly indicate that inulin was able to alter the composition of SCFA producing microbes, whereas tributyrin did not. This aligns with other studies that have shown that inulin can modulate the gut microbiome towards SCFA production41, whereas tributyrin has not been shown to specifically alter SCFA production. The inulin diet promoted a 58 significantly increase in acetic, lactic, succinic, and propionic acids, but no change in the concentrations of butyric and isovaleric acids in stool samples compared with the control group. Interestingly, butyric acid was the only SCFA with no significant difference between groups. The lower number of ASVs related to butyric acid production could explain the non-significant changes in amounts of butyric acid produced between the inulin/tributyrin and control groups. These findings lead to the question of the efficiency of the prebiotics inulin and tributyrin in stimulating SCFA production in the gut. Regarding oxalate concentrations in the urine, the inulin diet lead to a two fold reduction in average concentrations. This results indicate that inulin is somehow modulating the oxalate concentration in the urine. As demonstrated in our study, inulin leads to increased production of SCFAs and other research groups have shown reductions in urine oxalate levels after administering acetate, propionate and butyrate44. It has also been shown that SCFA administration is associated with the expression of SLC26A3 and SLC26A6 transporter genes (regulates oxalate excretion in the gut), of which acetate, propionate and butyrate are able to up-regulated SLC26A6 and down-regulated SLC26A3 expression in the ileum and cecum. These data suggest that SCFAs can reduce oxalate absorption by influencing the expression of genes related to oxalate transport in the gut. Another research group43 linked the administration of SCFA to a reduction of oxalate crystals via modulation of the immune response leading to increased frequency of CX3Cr1+CD24- macrophages and decreased GR1+ neutrophil infiltration in kidneys. Remarkable variations in oxalate absorption, microbiome and metabolite composition occurs along gastrointestinal tract37. Therefore, it is paramount when analyzing samples that the portion of the gut where the sample was collected is taken into consideration in order to adequately analyse the results. There was a noticeable variation in the microbiota between stool and cecal samples when comparing the inulin and control groups. In the stool samples of inulin fed mice we noticed a reduction in the differential abundance of the Lachnospiraceae family and an increase in Clostridia. Conversely, in the cecal samples 59 of inulin fed mice we observed an increase of Lachnospiraceae, Clostridia, and Romboutsia; three important taxa related to SCFA production. This indicates that butyrate producers are predominant in the cecum portion of the gut, showing that there is a relevant shift in the microbiota composition between cecum and colon. Possibly, the cecum environment is favourable for a greater number of SCFA producers. One important factor in the results found for microbiota data is the bioinfomatics methods and algorithms employed for it analysis. Comparing our results to different research37,41,43,44,45 the taxon related to inulin and to SCFAs supplementation are somewhat similar but there are still families and species that appear exclusively in some results but not consistently in all papers. Another factor is the lack of established taxonomic groups for SCFA producers and oxalate degraders, one example is noticed in the Neotoma45 microbiota research where there is a table of the taxa stimulated by oxalate, and the ones that had the greatest numbers of OTU's stimulated by oxalate were related to the S24-7 family (recently established as the Muribaculaceae family) and an unassigned one, both representing 76% of the OTU's stimulated by oxalate. Meaning that 33% of the oxalate degrading taxa have been only recent established (Muribaculaceae), and the other 43% are yet to be known and identified, showing that the gut microbiome field is quickly expanding. 60 5 Conclusion Inulin supplementation altered the microbiome by increasing the abundance of SCFA producers, which likely led to the higher acetic, lactic, succinic and propionic acid concentrations in the cecum. It was also noted that inulin supplementation modulated oxalate concentrations in the urine by reducing oxalate comparing with the control group, suggesting that inulin is a promising prebiotic treatment, and needs to be further investigated to better understand the effects of inulin/SCFA on kidney stone formation. The high oxalate diet reduced the alpha diversity and the relative abundance of some SCFA-producers, increased oxalate concentrations in the urine, and lead to the formation of crystalline structures in kidney tissue comparing with the control group. 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Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Lange, Dirk (Microbiologist)
How gut microbiome correlates with oxalate, butyrate and kidney stones formation
Text