Biology subjects

Burns, M. B.

Publications and source records attributed to Burns, M. B..

6 recordsLinked to original sources

bioRxiv2022

Revaluation of old data with new techniques reveals novel insights into the celiac microbiome

Celiac disease is an autoimmune disorder of the small intestine in which gluten, an energy-storage protein expressed by wheat and other cereals, elicits an immune response leading to villous atrophy. Despite a strong genetic component, the disease arises sporadically throughout life, leading us to hypothesize the the microbiome might be a trigger for celiac disease. Here, we took microbiome data from 3 prior studies examining celiac disease and the microbiome and analyzed this data with newer computational tools and databases: the dada2 and PICRUSt2 pipelines and the SILVA database. Our results both confirmed findings of previous studies and generated new data regarding the celiac microbiome of India and Mexico. Our results showed that, while some aspects of prior reports are robust, older datasets must be reanalyzed with new tools to ascertain which findings remain accurate while also uncovering new findings. IMPORTANCEBioinformatics is a rapidly developing field, with new computational tools released yearly. It is thus important to revisit results generated using older tools to determine whether they are also revealed by currently available technology. Celiac disease is an autoimmune disorder that affects up to 2% of the worlds population. While the ultimate cause of celiac disease is unknown, many researchers hypothesize that changes to the intestinal microbiome play a role in the diseases progression. Here, we have re-analyzed 16S rRNA data from several previous celiac studies to determine whether previous results are also uncovered using new computational tools.

bioinformatics↗

bioRxiv2022

Celiac dysbiosis does not transcend geographic boundaries

Celiac disease is an autoimmune disorder of the small intestine in which gluten, an energy-storage protein found in wheat and other cereals, elicits an immune response that leads to villous atrophy. Despite a strong genetic component, celiac disease arises sporadically and at any age, leading us to hypothesize that changes in the microbiome influence celiac disease development and/or progression. Here, we pooled and computationally analyzed 16S data from 3 prior international studies that examined celiac disease and the microbiome. For our analysis, we combined the dada2 and PICRUSt 2 pipelines and a variety of data transformations that control for batch effects to determine whether any taxonomic or metabolic features were consistently associated with the celiac microbiome across the globe. Our results showed the celiac microbiome displays dysbiosis without a discernable pattern, which suggests perturbations in the celiac microbiome are a result of the disease rather than a cause. Data from PICRUSt 2 supported this conclusion and revealed connections between celiac disease and the metabolome that are supported by previous research examining dysbiotic microbiomes. IMPORTANCECeliac disease is an autoimmune disorder that affects roughly 2% of the worlds population. Although the ultimate cause of celiac disease is unknown, many researchers hypothesize that changes to the intestinal microbiome play a key role in disease progression. If this is the case, it may be possible to design therapies that manipulate the microbiome to suppress celiac disease. Here, we analyzed pooled data from 3 different studies from across the globe that examined celiac disease and the microbiome to ascertain whether there exists a unique celiac microbiome that transcends geographic boundaries.

bioinformatics↗

bioRxiv2022

Integrating current analyses of the breast cancer microbiome

Breast cancer is the second leading cause of cancer death for women in the US (American Cancer Society: About Breast Cancer, n.d.). Many cancer types have significant associations with their resident microbial communities - emerging evidence suggests that breast cancers also interact with the local tissue-associated microbiota. Studies have examined the relationship between breast cancer and its microbiome, however, the studies varied in their approaches used to evaluate these relationships. Microbiome research advances rapidly and analysis pipelines and databases are updated frequently. This dynamic environment makes inter-study comparisons and superficial evaluations challenging as no two studies are using the same standards for evaluation. Researchers have observed the microbiota of tumor tissue, surrounding normal sites, and healthy breast tissue from non-cancer individuals (Hieken et al., 2016; Urbaniak et al., 2016; Xuan et al., 2014), but they have not been able to translate their findings into information that can be used for breast cancer treatment or detection nor address what affect studying different variable regions has in their analysis. Within the majority of these studies, comparisons of the tumor tissue with adjacent normal tissue has revealed differences. This project will integrate all available studies related to breast cancer and the mammary microbiome to 1 reassess the original findings in light of advances in this rapidly progressing field and 2 incorporate all the data available as a large meta-analysis to identify general trends and specific differences across patient cohorts and studies.

bioinformatics↗

bioRxiv2021

Shared and disease-specific host gene-microbiome interactions across human diseases

While the gut microbiome and host gene regulation separately contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here, we developed a machine learning-based framework to jointly analyze host transcriptomic and microbiome profiles from 416 colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease, and irritable bowel syndrome. We identified potential interactions between gut microbes and host genes that are disease-specific, as well as interactions that are shared across the three diseases, involving host genes and gut microbes previously implicated in gastrointestinal inflammation, gut barrier protection, energy metabolism, and tumorigenesis. In addition, we found that mucosal gut microbes that have been associated with all three diseases, such as Streptococcus, interact with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes.

genomics↗

bioRxiv2017

Variation in gut microbiota composition impacts host gene expression

Variation in gut microbiome is associated with wellness and disease in humans, yet the molecular mechanisms by which this variation affects the host are not well understood. A likely mechanism is through changing gene regulation in interfacing host epithelial cells. Here, we treated colonic epithelial cells with live microbiota from five healthy individuals and quantified induced changes in transcriptional regulation and chromatin accessibility in host cells. We identified over 5,000 host genes that change expression, including 588 distinct associations between specific taxa and host genes. The taxa with the strongest influence on gene expression alter the response of genes associated with complex traits. Using ATAC-seq, we show that a subset of these changes in gene expression are likely the result of changes in host chromatin accessibility and transcription factor binding induced by exposure to gut microbiota. We then created a manipulated microbial community with titrated doses of Collinsella, demonstrating that both natural and controlled microbiome composition leads to distinct, and predictable, gene expression profiles in host cells. Together, our results suggest that specific microbes play an important role in regulating expression of individual host genes involved in human complex traits. The ability to fine tune the expression of host genes by manipulating the microbiome suggests future therapeutic routes.

genomics↗

bioRxiv2016

Discrete mutations in colorectal cancer correlate with defined microbial communities in the tumor microenvironment

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. These results can serve as a starting point for fine-grained exploration of the functional interactions between discrete alterations in tumor DNA and proximal microbial communities in CRC. In addition, these findings can lead to the development of improved microbiome-based CRC screening methods, as well as individualized microbiota-targeting therapies.\n\nAuthor summaryAlthough the gut microbiome - the collection of microorganisms that inhabit our gastrointestinal tract - has been implicated in colorectal cancer, colorectal tumors are caused by genetic mutations in host DNA. Here, we explored whether various mutations in colorectal tumors are correlated with specific changes in the bacterial communities that live in and on these tumors. We find that the genes and biological pathways that are mutated in tumors are correlated with variation in the composition of the microbiome. In fact, these changes in the microbiome are consistent enough that we can use them to statistically predict tumor mutations solely based on the microbiome. Our results may be used to understand the roles of specific microbes in CRC biology, and could also be the starting point of microbiome-based diagnostics for not only detection of CRC, but characterization of tumor mutational profiles.

cancer biology↗