Decreased microbial co-occurrence network stability and SCFA receptor level correlates with obesity in African-origin women.

We compared the gut microbial populations in 100 women, from rural Ghana and urban US [50% lean (BMI < 25 kg/m2) and 50% obese (BMI ≥ 30 kg/m2)] to examine the ecological co-occurrence network topology of the gut microbiota as well as the relationship of short chain fatty acids (SCFAs) with obesity. Ghanaians consumed significantly more dietary fiber, had greater microbial alpha-diversity, different beta-diversity, and had a greater concentration of total fecal SCFAs (p-value < 0.002). Lean Ghanaians had significantly greater network density, connectivity and stability than either obese Ghanaians, or lean and obese US participants (false discovery rate (FDR) corrected p-value ≤ 0.01). Bacteroides uniformis was significantly more abundant in lean women, irrespective of country (FDR corrected p < 0.001), while lean Ghanaians had a significantly greater proportion of Ruminococcus callidus, Prevotella copri, and Escherichia coli, and smaller proportions of Lachnospiraceae, Bacteroides and Parabacteroides. Lean Ghanaians had a significantly greater abundance of predicted microbial genes that catalyzed the production of butyric acid via the fermentation of pyruvate or branched amino-acids, while obese Ghanaians and US women (irrespective of BMI) had a significantly greater abundance of predicted microbial genes that encoded for enzymes associated with the fermentation of amino-acids such as alanine, aspartate, lysine and glutamate. Similar to lean Ghanaian women, mice humanized with stool from the lean Ghanaian participant had a significantly lower abundance of family Lachnospiraceae and genus Bacteroides and Parabacteroides, and were resistant to obesity following 6-weeks of high fat feeding (p-value < 0.01). Obesity-resistant mice also showed increased intestinal transcriptional expression of the free fatty acid (Ffa) receptor Ffa2, in spite of similar fecal SCFAs concentrations. We demonstrate that the association between obesity resistance and increased predicted ecological connectivity and stability of the lean Ghanaian microbiota, as well as increased local SCFA receptor level, provides evidence of the importance of robust gut ecologic network in obesity

Applying Machine Learning Algorithms for the Analysis of Biological Sequences and Medical Records

The modern sequencing technology revolutionizes the genomic research and triggers explosive growth of DNA, RNA, and protein sequences. How to infer the structure and function from biological sequences is a fundamentally important task in genomics and proteomics fields. With the development of statistical and machine learning methods, an integrated and user-friendly tool containing the state-of-the-art data mining methods are needed. Here, we propose SeqFea-Learn, a comprehensive Python pipeline that integrating multiple steps: feature extraction, dimensionality reduction, feature selection, predicting model constructions based on machine learning and deep learning approaches to analyze sequences. We used enhancers, RNA N6- methyladenosine sites and protein-protein interactions datasets to evaluate the validation of the tool. The results show that the tool can effectively perform biological sequence analysis and classification tasks. Applying machine learning algorithms for Electronic medical record (EMR) data analysis is also included in this dissertation. Chronic kidney disease (CKD) is prevalent across the world and well defined by an estimated glomerular filtration rate (eGFR). The progression of kidney disease can be predicted if future eGFR can be accurately estimated using predictive analytics. Thus, I present a prediction model of eGFR that was built using Random Forest regression. The dataset includes demographic, clinical and laboratory information from a regional primary health care clinic. The final model included eGFR, age, gender, body mass index (BMI), obesity, hypertension, and diabetes, which achieved a mean coefficient of determination of 0.95. The estimated eGFRs were used to classify patients into CKD stages with high macro-averaged and micro-averaged metrics

The insect pathogen Serratia marcescens Db10 uses a hybrid non-ribosomal peptide synthetase-polyketide synthase to produce the antibiotic althiomycin

There is a continuing need to discover new bioactive natural products, such as antibiotics, in genetically-amenable micro-organisms. We observed that the enteric insect pathogen, Serratia marcescens Db10, produced a diffusible compound that inhibited the growth of Bacillis subtilis and Staphyloccocus aureus. Mapping the genetic locus required for this activity revealed a putative natural product biosynthetic gene cluster, further defined to a six-gene operon named alb1-alb6. Bioinformatic analysis of the proteins encoded by alb1-6 predicted a hybrid non-ribosomal peptide synthetase-polyketide synthase (NRPS-PKS) assembly line (Alb4/5/6), tailoring enzymes (Alb2/3) and an export/resistance protein (Alb1), and suggested that the machinery assembled althiomycin or a related molecule. Althiomycin is a ribosome-inhibiting antibiotic whose biosynthetic machinery had been elusive for decades. Chromatographic and spectroscopic analyses confirmed that wild type S. marcescens produced althiomycin and that production was eliminated on disruption of the alb gene cluster. Construction of mutants with in-frame deletions of specific alb genes demonstrated that Alb2-Alb5 were essential for althiomycin production, whereas Alb6 was required for maximal production of the antibiotic. A phosphopantetheinyl transferase enzyme required for althiomycin biosynthesis was also identified. Expression of Alb1, a predicted major facilitator superfamily efflux pump, conferred althiomycin resistance on another, sensitive, strain of S. marcescens. This is the first report of althiomycin production outside of the Myxobacteria or Streptomyces and paves the way for future exploitation of the biosynthetic machinery, since S. marcescens represents a convenient and tractable producing organism

A Rough Set-Based Model of HIV-1 Reverse Transcriptase Resistome

Reverse transcriptase (RT) is a viral enzyme crucial for HIV-1 replication. Currently, 12 drugs are targeted against the RT. The low fidelity of the RT-mediated transcription leads to the quick accumulation of drug-resistance mutations. The sequence-resistance relationship remains only partially understood. Using publicly available data collected from over 15 years of HIV proteome research, we have created a general and predictive rule-based model of HIV-1 resistance to eight RT inhibitors. Our rough set-based model considers changes in the physicochemical properties of a mutated sequence as compared to the wild-type strain. Thanks to the application of the Monte Carlo feature selection method, the model takes into account only the properties that significantly contribute to the resistance phenomenon. The obtained results show that drug-resistance is determined in more complex way than believed. We confirmed the importance of many resistance-associated sites, found some sites to be less relevant than formerly postulated and—more importantly—identified several previously neglected sites as potentially relevant. By mapping some of the newly discovered sites on the 3D structure of the RT, we were able to suggest possible molecular-mechanisms of drug-resistance. Importantly, our model has the ability to generalize predictions to the previously unseen cases. The study is an example of how computational biology methods can increase our understanding of the HIV-1 resistome

Engineering enzymes for noncanonical amino acid synthesis

The standard proteinogenic amino acids grant access to a myriad of chemistries that harmonize to create life. Outside of these twenty canonical protein building blocks are countless noncanonical amino acids (ncAAs), either found in nature or created by man. Interest in ncAAs has grown as research has unveiled their importance as precursors to natural products and pharmaceuticals, biological probes, and more. Despite their broad applications, synthesis of ncAAs remains a challenge, as poor stereoselectivity and low functional-group compatibility stymie effective preparative routes. The use of enzymes has emerged as a versatile approach to prepare ncAAs, and nature's enzymes can be engineered to synthesize ncAAs more efficiently and expand the amino acid alphabet. In this tutorial review, we briefly outline different enzyme engineering strategies and then discuss examples where engineering has generated new ‘ncAA synthases’ for efficient, environmentally benign production of a wide and growing collection of valuable ncAAs

Engineering enzymes for noncanonical amino acid synthesis

The standard proteinogenic amino acids grant access to a myriad of chemistries that harmonize to create life. Outside of these twenty canonical protein building blocks are countless noncanonical amino acids (ncAAs), either found in nature or created by man. Interest in ncAAs has grown as research has unveiled their importance as precursors to natural products and pharmaceuticals, biological probes, and more. Despite their broad applications, synthesis of ncAAs remains a challenge, as poor stereoselectivity and low functional-group compatibility stymie effective preparative routes. The use of enzymes has emerged as a versatile approach to prepare ncAAs, and nature's enzymes can be engineered to synthesize ncAAs more efficiently and expand the amino acid alphabet. In this tutorial review, we briefly outline different enzyme engineering strategies and then discuss examples where engineering has generated new ‘ncAA synthases’ for efficient, environmentally benign production of a wide and growing collection of valuable ncAAs

Transcriptional control of the H-NS antagonists LeuO and RcsB-BglJ in Escherichia coli

The bacterial nucleoid-associated protein (NAP) H-NS is involved in the organization and compaction of the bacterial chromatin and acts as a global respressor, mainly of genes that have been acquired by horizontal gene transfer and that are related to stress responses and pathogenicity. Binding of H-NS to the DNA and formation of a nucleoprotein complex at promoter regions leads to repression. This repressor effect of H-NS can be antagonized by gene-specific transcription factors (H-NS antagonists) that activate transcription of H NS-repressed genes by competing with H-NS for binding or by disturbing formation of the nucleoprotein complex. Two examples of such H NS antagonists are the LysR-type transcription factor LeuO and the FixJ/NarL-type transcription factor heterodimer RcsB-BglJ. LeuO is a pleiotropic regulator of stress responses and virulence determinants. RcsB-BglJ activates transcription of the H NS-repressed bgl (aryl-β,D-glucoside) operon. In this work, novel targets of RcsB-BglJ were identified in Escherichia coli by microarray analyses. The results suggest that heterodimerization of RcsB and BglJ is essential for regulation. Further, in addition to genes related to unknown or predicted function in the membrane the leuO gene was identified as a target gene. Detailed analysis of transcriptional regulation of leuO demonstrated that RcsB-BglJ strongly activates transcription of leuO by binding proximal to a newly mapped leuO promoter. Thus RcsB-BglJ antagonizes repression of leuO by H-NS and the H-NS-like protein StpA. Additional data presented here show that LeuO negatively autoregulates its own expression and inhibits activation of leuO by RcsB-BglJ. Regulation of leuO by RcsB-BglJ and autoregulation by LeuO, as shown here, as well as activation of bglJ by LeuO, as published previously, indicates a feedback control mechanism of two global transcriptional regulators and H-NS antagonists.This feedback regulation may ensure turn on of their expression in response to specific environmental signals. Screens to search for novel regulators or upstream signals were performed by transposon mutagenesis and by using a genomic expression library. These screens indicate that additional factors may be involved in the regulation of this leuO-bglJ feedback loop

Methods For Inhibiting Clc-2 Channel With Gatx2

Compositions and methods of using scorpion venom peptide that is a ligand for ClC channels are provided. One aspect provides a pharmaceutical composition containing an amount of GaTx2 effective to inhibit ClC activity. Methods of treating a disorder or symptom of a disorder related to aberrant ClC channel activity are also provided.Georgia Tech Research Corporatio