Investigating Restoration of Gut Microbiota and Symptom Amelioration in Murine Models of Autism
There has been a dramatic increase in the occurrence of Autism Spectrum Disorder (ASD) over recent decades. Prevalence has increased from .045% amongst children in 1996 to 14.7% in 2010(Mayer et al., 2014). The rise in prevalence of ASD has fueled research into understanding the physiological mechanisms, identifying possible risk factors, determining useful biomarkers for diagnosis, and developing possible treatments. Despite the heightened interest, much is left to be understood in regards to ASD.
However, there have been several studies noting an apparent relationship between ASD and gastrointestinal disorders(Parracho et al., 2005; Adams et al., 2011; Coury et al., 2012). This correlation, in addition to heavily processed western diets, increased antibiotic use, and modern hygienic conditions have prompted research into the role of the microbiome in chronic illnesses and disorders such as ASD. Comparison of gut and fecal microbiota analyses in ASD and non-ASD individuals has provided evidence of significant differences in the abundance of key species(Cao et al., 2013; Mayer et al., 2014). Several studies have identified Clostridium and Desulfovibrio spp. as possible influences of developing ASD (Song et al., 2004; Parracho et al., 2005; Finegold et al., 2010, 2012; Adams et al., 2011; Finegold, 2011a; Siqueira et al., 2012; Tomova et al., 2015).
Growing support of the microbiota’s role in neurobehavioral disorders such as ASD has prompted the questioning of possible prevention or treatment of ASD through the use of probiotics. The reasoning behind this hypothesis is the documented ability of probiotics to manipulate the microbiome in potentially beneficial ways(Fuentes et al., 2008; Zavisic et al., 2012; Wang et al., 2014; Zhang et al., 2014). These hypotheses have begun to gain merit following a recent study that not only showed a positive effect of certain probiotics on gut composition, but actually relieved ASD symptoms in mice models(Hsiao et al., 2013).
These findings and developing understanding of the microbiota and autism have prompted me to investigate further into the correlation of disrupted gut composition and ASD. Additionally, I plan to build on the recent probiotic study(Hsiao et al., 2013), and test if a group of probiotics are also capable of restoring gut composition and relieving symptom severity in a different ASD mice model.
If this and future studies can provide further evidence that probiotics are capable of relieving ASD symptom severity, this information will bring the scientific community much closer to a possible cure or effective treatment of this burdening disease. Not only would behavioral-symptom treatment improve, but the severe gastrointestinal issues that accompany the disorder could be more efficiently targeted with proper probiotics. These advances could greatly increase the quality of life in Autism Spectrum Disorder individuals, and help prevent a prolonged increase in prevalence for future generations.
Introduction, Background, and Significance
Autism Spectrum Disorder (ASD) describes a set of developmental disorders varying in severity between individuals and result in a range of social and communication deficits, as well as repetitive behavior (Tomova et al., 2015). ASD is often accompanied with comorbid disorders, adding a greater burden to diagnosed individuals. Among these additional disorders, up to 90% of ASD individuals experience gastrointestinal disorders such as diarrhea, reflux, and vomiting[Parracho et al., 2005; Coury et al., 2012]. Additionally, the intensity of gastrointestinal symptoms have been shown to correlate with the severity of ASD symptoms (Adams et al., 2011).
The relation of GI disorders to ASD has prompted much research into a comparison of gut microflora composition of ASD and healthy individuals. Many identifiable differences have been observed within Bacteroidetes, Firmicutes, and Proteobacteria, which constitute the majority of gut and fecal microflora (Cao et al., 2013; Mayer et al., 2014). Prevalence and differences in proportions of specific families within each classification have offered insight into the role of altered gut microbiota in ASD.
Gut Microbiota in ASD
One key finding is an increased proportion of Clostridia spp. in ASD patients (Song et al., 2004; Parracho et al., 2005). These bacterium have been thought to play a possible role in the development of ASD due to their production of toxins and virulent production of spores(Finegold, 2011b). Clostridia belong to Firmicutes and further evidence suggests that this phylum may contain potentially harmful bacteria that may contribute to the development of ASD (Finegold et al., 2010). Other studies have supported the potential impact of Firmicutes with findings of a decreased Bacteroides/Firmicutes ratio in ASD microflora, and an overall increased abundance of Bacteroides in non-ASD microflora (Finegold et al., 2010; Williams et al., 2012; Zhang et al., 2014; Tomova et al., 2015). Not only do these findings suggest that increased Firmicutes abundance may correlate with ASD, but that Bacteroides may play a beneficial role in ASD prevention.
Another key insight gained from ASD microbiota analyses is the potential importance of Desulfovibrio spp. Like Clostridia, Desulfovibrio produce virulent factors such as lipopolysaccharides and reduces sulfur to produce toxic hydrogen peroxide, decreasing the availability of sulfur for host physiological processes (Finegold et al., 2012; Gondalia et al., 2012). Increased abundance of this species has been observed in ASD individuals and has been hypothesized to be play a causal role in the onset of ASD (Finegold et al., 2010, 2012; Adams et al., 2011; Siqueira et al., 2012). Additionally, abundance of Desulfovibrio in ASD patients has been correlated to the severity of ASD symptoms, specifically repetitive behavior (Tomova et al., 2015). These findings of altered gut microflora within ASD patients provide a framework for possible methods to study plausible causes and mechanisms of ASD development.
Murine Models of ASD
In addition to analysis of gut composition in humans, mice models exhibiting ASD like traits allow further study into the role of microbiota in autism. C58/J and BALB/c mice are two phenotype-first models, meaning the traits have been induced solely through selective breeding, and are quite useful. C58/J exhibit traits of reduced sociability and learning deficits, while BALB/c mice show reduced social interaction and repetitive behavior. Additionally, a subset of BALB/c mice (BALB/cJ) are highly aggressive and more importantly experience gastrointestinal abnormalities (Argyropoulos et al., 2013).
These models can be further modified to produce offspring that are more analogous to ASD and thus more useful in the investigation of ASD gut composition (Fig 1.) One example is the Maternal Immune Activation model (MIA), which is based on evidence that maternal viral infection greatly increases risk of autism in offspring [Atladóttir et al., 2010]. When pregnant mice are injected with a viral mimic, offspring exhibit ASD-like symptoms including repetitive behavior and social deficits (Malkova et al., 2012). Another modified model is the Valproic Acid model (VPA), in which prenatal exposure to VPA produces offspring with ASD like symptoms. More importantly, this prenatal VPA exposure also induces alterations in gut microbiota composition resembling changes found in human ASD individuals. Specifically, VPA exposed offspring exhibit an increased abundance of Desulfovibrio spp. and Clostridium spp. (de Theije et al., 2014).These findings that MIA and VPA models exhibit altered microbiota composition lend greater support of a link between ASD and the gut microbiota.
Fig. 1. Two mice models of autism. Both produce ASD like symptoms in offspring of BALB/c mice. Valproic acid will be used to induce ASD-like mice in this study
Because Desulfovibrio and Clostridium are quite resistant to antibiotics and are found in increased abundance for ASD individuals, research into the effect of specific probiotics on these species is warranted in order to gain a better understanding of the role of microbiota in ASD and progress toward an effective treatment [Finegold et al., 2010, 2012; Finegold, 2011a]. Studies have shown that treatment of Lactobacillus plantarum and Lactobacillus casei were shown to decrease Desulfovibrio and Clostridium abundance in human adults, respectively (Wang et al., 2014; Zhang et al., 2014). These probiotics have also been shown to be effective at altering the gut composition within mice models and so may be good candidates for studying the effect of probiotics on ASD-like mice models (Fuentes et al., 2008; Zavisic et al., 2012). Although there have been no studies of these Lactobacilli in ASD models, there was recently a groundbreaking study using the treatment of Bacteroides fragilis on MIA model offspring. MIA offspring exhibited altered gut composition including higher levels of Clostridium when compared to non-MIA offspring and gut composition of the MIA offspring was then restored to normal abundances after B. fragilis treatment. Shockingly, this restoration of the gut composition was accompanied by improvement in behavioral tests indicating an amelioration in ASD-like behavior (Hsiao et al., 2013).
Evidence of B. fragilis restoring MIA offspring gut composition to non-MIA proportions and reducing ASD symptoms proposes investigation of similar treatments in other ASD mice models such as VPA. Because VPA offspring exhibit higher relative abundances of Clostridium and Desulfovibrio, and L. casei and L. plantarum reduce levels of these bacteria respectively in humans, two questions warrant investigation. Can L. plantarum or L. casei restore microbiota composition in VPA exposed mice like B. fragilis does for MIA mice? And if so, can this restoration alleviate ASD-like symptoms in the mice? The answers of these questions may have great implications in our understanding of ASD and possible treatments. Alleviation of ASD symptoms in response to restoration of gut composition would provide significant more evidence of the role of gut microbiota in ASD and other neurobehavioral disorders like schizophrenia. Further research would be necessary to document the possible physiological consequences of altered microbiota, such as shortage or excess of specific metabolites. Additionally, the evidence of a role of Clostridium and Desulfovibrio in the development of ASD would warrant further research into how these species become more abundant and how they interact with other bacteria and affect digestion and metabolism. Also, similar studies into the use of other probiotics would be greatly beneficial in identifying these relationships between species of the microbiota and additional potential treatments. Lastly, a repeat of this study in ASD humans would be hugely beneficial. If the results in humans are consistent with the possible results of this study, a potentially efficient treatment model involving L. plantarum, L. casei, B fragilis, and other effective probiotics may be implemented in clinical trials. Alleviation of ASD symptoms via alteration of the gut would represent a drastic step forward in the treatment of autism.
Project Objectives, Hypothesis, Predictions
In order to study the correlation of altered microbiota composition with behavioral deficits of ASD mice models and to investigate the potential of probiotics as an alleviating treatment, the following hypotheses are proposed. Increased abundances of Clostridium and Desulfovibrio in offspring of mice exposed to VPA can be restored to normal levels with probiotic treatment of L. casei and L. plantarum because they are known to reduce abundances of Clostridium and Desulfovibrio respectively. If this primary hypothesis is supported, it is then reasonable to propose the restored abundances of Clostridium and Desulfovibrio in offspring of mice exposed to VPA will ameliorate the severity of ASD-like symptoms because of unknown physiological mechanisms linking microbiota and ASD. If the primary hypothesis is true: Offspring of mice exposed to VPA that are given L. casei will have relative abundances of Clostridium restored to those of mice that were not exposed to VPA Offspring of mice exposed to VPA that are given L. plantarum will have relative abundances of Desulfovibrio restored to those of mice that were not exposed to VPA Mice given both probiotics will have rela1ve abundances of both Clostridium and Desulfovibrio restored to those of mice that were not exposed to VPA Mice given neither probiotic will maintain the elevated abundances of Clostridium and Desulfovibrio which will not be restored to non VPA proportions
If the first hypothesis is proven false and increased abundances of Clostridium and Desulfovibrio in Offspring of mice exposed to VPA cannot be restored through the use of probiotics then mice given one or both probiotics will maintain the elevated abundances of Clostridium and Desulfovibrio, which will not be restored to non-VPA proportions. If both the primary and secondary hypotheses are supported then VPA exposed offspring with restored microbiota composition will perform better on behavioral tests after probiotic treatment than before treatment. If the secondary hypothesis is false, then mice with restored microbiota composition will show no improvement or perform worse in behavioral tests after probiotic treatment than before treatment.
Experimental Procedures and Data Analysis
Fig 2. Schematic representation of procedure, treatment groups and predictions.
Inducing ASD Mice and Behavioral Tests
In order to induce ASD like symptoms as well as an altered gut microbiota in mice, pregnant BALB/c mice will be cared for and injected with either VPA or a saline solution as previously described (de Theije et al., 2014). This will result in offspring exhibiting ASD-like behavior and symptoms (including microbiota composition) as well as a control offspring group. These offspring will be selected from and serve as the samples for data collection.
Before selection, offspring from both groups will be assed for social deficits, as well as compulsive and repetitive behavior using established behavioral testing methods (Smith et al., 2007; Thomas et al., 2009; Malkova et al., 2012; Desbonnet et al., 2014) Sociability will be measured using the three chamber social test, in which individual mice are filmed and evaluated on the amount time they choose to spend in an empty chamber compared to a chamber containing other mice (Smith et al., 2007; Silverman et al., 2010; Desbonnet et al., 2014). Repetitive and compulsive behavior will be quantified using the self-grooming and marble burying tests, respectively (Thomas et al., 2009; Malkova et al., 2012). ASD offspring are expected to exhibited lower scores in all tests (Malkova et al., 2012; Argyropoulos et al., 2013; Kataoka et al., 2013). Behavioral tests will be performed prior to and following probiotic administration.
Probiotic Administration to Treatment Groups
Following the first set of behavioral testing, eight VPA offspring exhibiting decreased social and behavioral scores will each be randomly assigned to one of four treatment groups (Fig. 2). One group will receive only L. casei, one will receive only L. plantarum, one will receive both probiotics, and the last group will act as a positive control and receive neither probiotic. The probiotic will be administered in consistent doses with standard food pellets as previously described (Hsiao et al., 2013). The treatment will last 21 days, as this amount of time was previously shown to induce changes in gut composition(Fuentes et al., 2008).
Eight control offspring will be randomly assigned to be used as the control group, and will serve as a point of comparison for treatment groups (Fig. 2).
In order to evaluate and compare the composition of the microbiota between VPA and control offspring, fecal DNA of individuals within each group will be extracted from fresh feces via the bead-beating method using a QIAMP DNA Stool Mini-kit (Tanaka et al., 2009). DNA extraction will take place before probiotic administration and after the 21-day period in order to assess changes in relative abundances of Clostridia and Desulfovibrio species within VPA offspring as a result of probiotic treatment. These changes will be observed by utilizing quantitative PCR.
Measuring Abundances of Bacterial Groups
Relative abundances of Clostridia and Desulfovibrio groups will be calculated utilizing the Quantitative Polymerase Chain Reaction (qPCR). This is a widely known method used to specifically amplify selected DNA sequences present within fecal samples. Clostridia and Desulfovibrio DNA sequences will be targeted for amplification using commercially available group-specific primers as previously described (Matsuki et al., 2004; Wang et al., 2014). Each execution of qPCR will run for 40 cycles under manufacturer described conditions, producing comparable amplifications between all samples. The quantity of amplified DNA for the control and all ASD groups will be compared to a standard curve created from amplifications of a known Escherichia coli primer dilution series. By normalizing the weight of a sample’s amplified DNA against a standard curve of known bacteria colony dilutions, an abundance of each species per sampled fecal weight will be extrapolated as previously described (Tanaka et al., 2009; Ellekilde et al., 2014; Wang et al., 2014). Treatment group abundances will then be compared to the control (non-ASD) abundances to yield a difference that represents the relative abundance of each species. DNA extraction and subsequent relative abundance calculations via qPCR will occur before and after probiotic treatment.
Before probiotic treatment:
The calculated abundances of Clostridia and Desulfovibrio will be averaged for ASD and control offspring. Differences between the ASD and control means will be used to calculate relative abundance of each species. These differences will then be analyzed for statistical significance using Fisher's exact test to confirm the predicted increased relative abundance of Clostridia and Desulfovibrio in VPA induced BALB/c models of ASD (de Theije et al., 2014). Fisher’s exact test will also be used to determine the significance of differences between the mean abundances of control and individual treatment groups before probiotic treatment. These differences represent the initial relative abundances to which post-treatment relative abundances will be compared.
After probiotic treatment:
The above analysis will be repeated for each treatment group after probiotic treatment. The difference between the control and individual treatment group mean abundances will represent the relative species abundance after probiotic treatment and be tested for significance with a Fisher’s exact test. Pre-treatment and post-treatment relative abundances will then be compared within each group and the difference will be tested for significance using a paired-t test. A significant decrease will indicate that the administered probiotic(s) is able to reduce the respective species abundance. Additionally, the decrease in abundance can be compared across treatment groups to identify which were most effective at decreasing elevated levels of Clostridia or Desulfovibrio and tested for significance using a one-way ANOVA test.
Assessment of species abundance restoration
To confirm if a probiotic treatment was able to restore species abundance to control (non-ASD) levels, mean relative abundance of a species within a treatment group must be observed to decrease significantly over treatment. Post-treatment abundance must not be significantly different from the control abundance
Analysis of social and behavioral testing
Social and behavioral test results will be compared before and after probiotic treatment within each treatment group. Significant changes will be determined using a paired t-test. Any significant improvements will indicate an amelioration of social behavioral deficits associated with autism in ASD model mice. Mean improvements resulting from each treatment will be compared across treatment groups using a one-way ANOVA to determine if which probiotic(s) were significantly more effective.
Feasibility, Timeline, and Budget
The more expensive technology required for this study can be found in the Biotechnology Labs at Cal Poly and greatly reduce the cost. The rest of the equipment is relatively inexpensive and can be easily purchased, with the listed price delivering a surplus. The financial cost of $1,064.28 is a small investment for research that may provide novel information into future ASD treatments. Findings from this study will provide greater insight into the mechanisms of autism, and have the potential to be utilized in clinical trials on human subjects that may lead to effective treatment of ASD symptoms. Future treatments used to ameliorate these symptoms could have a profoundly positive effect on Autism individuals, offering an improved quality of life.
Adams, J. B., L. J. Johansen, L. D. Powell, D. Quig, and R. A. Rubin (2011), Gastrointestinal flora and gastrointestinal status in children with autism--comparisons to typical children and correlation with autism severity., BMC Gastroenterol., 11(1), 22, doi:10.1186/1471-230X-11-22. Argyropoulos, A., K. L. Gilby, and E. L. Hill-Yardin (2013), Studying autism in rodent models: reconciling endophenotypes with comorbidities., Front. Hum. Neurosci., 7, 417, doi:10.3389/fnhum.2013.00417. Atladóttir, H. O., P. Thorsen, L. Østergaard, D. E. Schendel, S. Lemcke, M. Abdallah, and E. T. Parner (2010), Maternal infection requiring hospitalization during pregnancy and autism spectrum disorders., J. Autism Dev. Disord., 40(12), 1423–30, doi:10.1007/s10803-010-1006-y. Cao, X., P. Lin, P. Jiang, and C. Li (2013), Characteristics of the gastrointestinal microbiome in children with autism spectrum disorder: a systematic review., Shanghai Arch. psychiatry, 25(6), 342–53, doi:10.3969/j.issn.1002-0829.2013.06.003. Coury, D. L., P. Ashwood, A. Fasano, G. Fuchs, M. Geraghty, A. Kaul, G. Mawe, P. Patterson, and N. E. Jones (2012), Gastrointestinal conditions in children with autism spectrum disorder: developing a research agenda., Pediatrics, 130 Suppl (Supplement_2), S160–8, doi:10.1542/peds.2012-0900N. Desbonnet, L., G. Clarke, F. Shanahan, T. G. Dinan, and J. F. Cryan (2014), Microbiota is essential for social development in the mouse., Mol. Psychiatry, 19(2), 146–8, doi:10.1038/mp.2013.65. Ellekilde, M. et al. (2014), Transfer of gut microbiota from lean and obese mice to antibiotic-treated mice., Sci. Rep., 4, 5922, doi:10.1038/srep05922. Finegold, S. M. (2011a), Desulfovibrio species are potentially important in regressive autism., Med. Hypotheses, 77(2), 270–4, doi:10.1016/j.mehy.2011.04.032. Finegold, S. M. (2011b), State of the art; microbiology in health and disease. Intestinal bacterial flora in autism., Anaerobe, 17(6), 367–8, doi:10.1016/j.anaerobe.2011.03.007. Finegold, S. M. et al. (2010), Pyrosequencing study of fecal microflora of autistic and control children., Anaerobe, 16(4), 444–53, doi:10.1016/j.anaerobe.2010.06.008. Finegold, S. M., J. Downes, and P. H. Summanen (2012), Microbiology of regressive autism., Anaerobe, 18(2), 260–2, doi:10.1016/j.anaerobe.2011.12.018. Fuentes, S., M. Egert, M. Jiménez-Valera, A. Ramos-Cormenzana, A. Ruiz-Bravo, H. Smidt, and M. Monteoliva-Sanchez (2008), Administration of Lactobacillus casei and Lactobacillus plantarum affects the diversity of murine intestinal lactobacilli, but not the overall bacterial community structure., Res. Microbiol., 159(4), 237–43, doi:10.1016/j.resmic.2008.02.005. Gondalia, S. V, E. A. Palombo, S. R. Knowles, S. B. Cox, D. Meyer, and D. W. Austin (2012), Molecular characterisation of gastrointestinal microbiota of children with autism (with and without gastrointestinal dysfunction) and their neurotypical siblings., Autism Res., 5(6), 419–27, doi:10.1002/aur.1253. Hsiao, E. Y. et al. (2013), Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders., Cell, 155(7), 1451–63, doi:10.1016/j.cell.2013.11.024. Kataoka, S., K. Takuma, Y. Hara, Y. Maeda, Y. Ago, and T. Matsuda (2013), Autism-like behaviours with transient histone hyperacetylation in mice treated prenatally with valproic acid., Int. J. Neuropsychopharmacol., 16(1), 91–103, doi:10.1017/S1461145711001714. Malkova, N. V, C. Z. Yu, E. Y. Hsiao, M. J. Moore, and P. H. Patterson (2012), Maternal immune activation yields offspring displaying mouse versions of the three core symptoms of autism., Brain. Behav. Immun., 26(4), 607–16, doi:10.1016/j.bbi.2012.01.011. Matsuki, T., K. Watanabe, J. Fujimoto, T. Takada, and R. Tanaka (2004), Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in human feces., Appl. Environ. Microbiol., 70(12), 7220–8, doi:10.1128/AEM.70.12.7220-7228.2004. Mayer, E. A., D. Padua, and K. Tillisch (2014), Altered brain-gut axis in autism: comorbidity or causative mechanisms?, Bioessays, 36(10), 933–9, doi:10.1002/bies.201400075. Parracho, H. M. R. T., M. O. Bingham, G. R. Gibson, and A. L. McCartney (2005), Differences between the gut microflora of children with autistic spectrum disorders and that of healthy children., J. Med. Microbiol., 54(Pt 10), 987–91, doi:10.1099/jmm.0.46101-0. Silverman, J. L., M. Yang, C. Lord, and J. N. Crawley (2010), Behavioural phenotyping assays for mouse models of autism., Nat. Rev. Neurosci., 11(7), 490–502, doi:10.1038/nrn2851. Siqueira, J. F., A. F. Fouad, and I. N. Rôças (2012), Pyrosequencing as a tool for better understanding of human microbiomes., J. Oral Microbiol., 4, doi:10.3402/jom.v4i0.10743. Smith, S. E. P., J. Li, K. Garbett, K. Mirnics, and P. H. Patterson (2007), Maternal immune activation alters fetal brain development through interleukin-6., J. Neurosci., 27(40), 10695–702, doi:10.1523/JNEUROSCI.2178-07.2007. Song, Y., C. Liu, and S. M. Finegold (2004), Real-time PCR quantitation of clostridia in feces of autistic children., Appl. Environ. Microbiol., 70(11), 6459–65, doi:10.1128/AEM.70.11.6459-6465.2004. Tanaka, S., T. Kobayashi, P. Songjinda, A. Tateyama, M. Tsubouchi, C. Kiyohara, T. Shirakawa, K. Sonomoto, and J. Nakayama (2009), Influence of antibiotic exposure in the early postnatal period on the development of intestinal microbiota., FEMS Immunol. Med. Microbiol., 56(1), 80–7, doi:10.1111/j.1574-695X.2009.00553.x. De Theije, C. G. M., H. Wopereis, M. Ramadan, T. van Eijndthoven, J. Lambert, J. Knol, J. Garssen, A. D. Kraneveld, and R. Oozeer (2014), Altered gut microbiota and activity in a murine model of autism spectrum disorders., Brain. Behav. Immun., 37, 197–206, doi:10.1016/j.bbi.2013.12.005. Thomas, A., A. Burant, N. Bui, D. Graham, L. A. Yuva-Paylor, and R. Paylor (2009), Marble burying reflects a repetitive and perseverative behavior more than novelty-induced anxiety, Psychopharmacology (Berl)., 204, 361–373, doi:10.1007/s00213-009-1466-y. Tomova, A., V. Husarova, S. Lakatosova, J. Bakos, B. Vlkova, K. Babinska, and D. Ostatnikova (2015), Gastrointestinal microbiota in children with autism in Slovakia., Physiol. Behav., 138, 179–87, doi:10.1016/j.physbeh.2014.10.033. Wang, L., J. Zhang, Z. Guo, L. Kwok, C. Ma, W. Zhang, Q. Lv, W. Huang, and H. Zhang (2014), Effect of oral consumption of probiotic Lactobacillus planatarum P-8 on fecal microbiota, SIgA, SCFAs, and TBAs of adults of different ages., Nutrition, 30(7-8), 776–83.e1, doi:10.1016/j.nut.2013.11.018. Williams, B. L., M. Hornig, T. Parekh, and W. I. Lipkin (2012), Application of novel PCR-based methods for detection, quantitation, and phylogenetic characterization of Sutterella species in intestinal biopsy samples from children with autism and gastrointestinal disturbances., MBio, 3(1), doi:10.1128/mBio.00261-11. Zavisic, G., S. Petricevic, Z. Radulovic, J. Begovic, N. Golic, L. Topisirovic, and I. Strahinic (2012), Probiotic features of two oral Lactobacillus isolates., Braz. J. Microbiol., 43(1), 418–28, doi:10.1590/S1517-838220120001000050. Zhang, J., L. Wang, Z. Guo, Z. Sun, Q. Gesudu, L. Kwok, Menghebilige, and H. Zhang (2014), 454 pyrosequencing reveals changes in the faecal microbiota of adults consuming Lactobacillus casei Zhang., FEMS Microbiol. Ecol., 88(3), 612–22, doi:10.1111/1574-6941.12328.