The Human Microbiome in Chronic Kidney Disease: A Double-Edged Sword

Chronic kidney disease (CKD) is an increasing global health burden. Current treatments for CKD include therapeutics to target factors that contribute to CKD progression, including renin–angiotensin–aldosterone system inhibitors, and drugs to control blood pressure and proteinuria control. Recently, associations between chronic disease processes and the human microbiota and its metabolites have been demonstrated. Dysbiosis—a change in the microbial diversity—has been observed in patients with CKD. The relationship between CKD and dysbiosis is bidirectional; gut-derived metabolites and toxins affect the progression of CKD, and the uremic milieu affects the microbiota. The accumulation of microbial metabolites and toxins is linked to the loss of kidney functions and increased mortality risk, yet renoprotective metabolites such as short-chain fatty acids and bile acids help restore kidney functions and increase the survival rate in CKD patients. Specific dietary interventions to alter the gut microbiome could improve clinical outcomes in patients with CKD. Low-protein and high-fiber diets increase the abundance of bacteria that produce short-chain fatty acids and anti-inflammatory bacteria. Fluctuations in the urinary microbiome are linked to increased susceptibility to infection and antibiotic resistance. In this review, we describe the potential role of the gut, urinary and blood microbiome in CKD pathophysiology and assess the feasibility of modulating the gut microbiota as a therapeutic tool for treating CKD.

Bacterial-Viral Interactions in Human Orodigestive and Female Genital Tract Cancers: A Summary of Epidemiologic and Laboratory Evidence

Infectious agents, including viruses, bacteria, fungi, and parasites, have been linked to pathogenesis of human cancers, whereas viruses and bacteria account for more than 99% of infection associated cancers. The human microbiome consists of not only bacteria, but also viruses and fungi. The microbiome co-residing in specific anatomic niches may modulate oncologic potentials of infectious agents in carcinogenesis. In this review, we focused on interactions between viruses and bacteria for cancers arising from the orodigestive tract and the female genital tract. We examined the interactions of these two different biological entities in the context of human carcinogenesis in the following three fashions: (1) direct interactions, (2) indirect interactions, and (3) no interaction between the two groups, but both acting on the same host carcinogenic pathways, yielding synergistic or additive effects in human cancers, e.g., head and neck cancer, liver cancer, colon cancer, gastric cancer, and cervical cancer. We discuss the progress in the current literature and summarize the mechanisms of host-viral-bacterial interactions in various human cancers. Our goal was to evaluate existing evidence and identify gaps in the knowledge for future directions in infection and cancer.

Adaptive and powerful microbiome multivariate association analysis via feature selection

ABSTRACT The important role of human microbiome is being increasingly recognized in health and disease conditions. Since microbiome data is typically high dimensional, one popular mode of statistical association analysis for microbiome data is to pool individual microbial features into a group, and then conduct group-based multivariate association analysis. A corresponding challenge within this approach is to achieve adequate power to detect an association signal between a group of microbial features and the outcome of interest across a wide range of scenarios. Recognizing some existing methods’ susceptibility to the adverse effects of noise accumulation, we introduce the Adaptive Microbiome Association Test (AMAT), a novel and powerful tool for multivariate microbiome association analysis, which unifies both blessings of feature selection in high-dimensional inference and robustness of adaptive statistical association testing. AMAT first alleviates the burden of noise accumulation via distance correlation learning, and then conducts a data-adaptive association test under the flexible generalized linear model framework. Extensive simulation studies and real data applications demonstrate that AMAT is highly robust and often more powerful than several existing methods, while preserving the correct type I error rate. A free implementation of AMAT in R computing environment is available at https://github.com/kzb193/AMAT.

Human Microbiome and Its Medical Applications

The commensal microbiome is essential for human health and is involved in many processes in the human body, such as the metabolism process and immune system activation. Emerging evidence implies that specific changes in the microbiome participate in the development of various diseases, including diabetes, liver diseases, tumors, and pathogen infections. Thus, intervention on the microbiome is becoming a novel and effective method to treat such diseases. Synthetic biology empowers researchers to create strains with unique and complex functions, making the use of engineered microbes for clinical applications attainable. The aim of this review is to summarize recent advances about the roles of the microbiome in certain diseases and the underlying mechanisms, as well as the use of engineered microbes in the prevention, detection, and treatment of various diseases.

Validation that human microbiome phages use alternative genetic coding with TAG stop read as Q

Metagenomic findings suggesting that bacteriophages (phages) can use genetic codes different from those of their host bacteria reveal a new dimension of phage-host interaction dynamics. Whereas reassignment of stop codons to code for amino acids has been predicted, there has been no proteomic validation of alternative coding in phages. In fact, one code where the stop codon TAG is reassigned to glutamine (code 15) has never been experimentally validated in any biological system. Here, we characterized stop codon reassignment in two crAss-like phages found in the human gut microbiome using LC-MS/MS-based metaproteomics. The proteome data from several phage structural proteins clearly demonstrates reassignment of the TAG stop codon to glutamine, establishing for the first time the expression of genetic code 15.

Tumor Tissue-Specific Bacterial Biomarker Panel for Colorectal Cancer: Bacteroides Massiliensis, Alistipes Species, Alistipes Onderdonkii, Bifidobacterium Pseudocatenulatum, Corynebacterium Appendicis

Human microbiome studies have shown diversity to exist among different ethnic populations. However, studies pertaining to the microbial composition of CRC among the Indian population have not been well explored. We aimed to decipher the microbial signature in tumor tissues from North Indian CRC patients. Next-generation sequencing of tumor and adjacent tissue derived bacterial 16s rRNA V3-V4 hypevariable regions was performed to investigate the abundance of specific microbes. The expression profile analysis deciphered a decreased diversity among the tumor-associated microbial communities, and at the phyla level, Proteobacteria was differentially expressed in CRC tissues than adjacent normal. Further, DESeq2 normalization identified 4 out of 79 distinct species (p<0.005) only in CRC, Bacteroides massiliensis, Alistipes onderdonkii, Bifidobacterium pseudocatenulatum, and Corynebacterium appendicis. Thus, our findings suggest the use of these microbial signatures as putative biomarkers that can distinguish CRC tissues from their adjacent normal, which may shed light on the pathogenesis of CRC.

A Comprehensive Review on the Role of the Gut Microbiome in Human Neurological Disorders

The human body is full of an extensive number of commensal microbes, consisting of bacteria, viruses, and fungi, collectively termed the human microbiome. The initial acquisition of microbiota occurs from both the external and maternal environments, and the vast majority of them colonize the gastrointestinal tract (GIT).