Bacterial genome annotation

Untangling human milk oligosaccharides and infant gut microbiome

The developing gut microbiome in infancy plays a key role in shaping the host immune system and metabolic state, and human milk is the main factor influencing its composition. Human milk does not only serve to feed the baby, but also to help the new-born adapt to its new environment and microbial exposures. Human milk protects the infant by providing multiple bioactive molecules, including human milk oligosaccharides (HMOs), which are the third most abundant solid component after lipids and lactose. The infant is unable to digest HMOs, so they reach the small and large intestines intact where they have many roles, including acting as prebiotics. Bifidobacterium spp. are the main, but not the only, commensals equipped with genes for HMO degradation. In this review we will outline the HMOs structures and functions, list the genes needed for their digestion, and describe the main strategies adopted by bacteria for their utilization.

SFannotation: A Simple and Fast Protein Function Annotation System

Owing to the generation of vast amounts of sequencing data by using cost-effective, high-throughput sequencing technologies with improved computational approaches, many putative proteins have been discovered after assembly and structural annotation. Putative proteins are typically annotated using a functional annotation system that uses extant databases, but the expansive size of these databases often causes a bottleneck for rapid functional annotation. We developed SFannotation, a simple and fast functional annotation system that rapidly annotates putative proteins against four extant databases, Swiss-Prot, TIGRFAMs, Pfam, and the non-redundant sequence database, by using a best-hit approach with BLASTP and HMMSEARCH.

Modeling the differences in biochemical capabilities of pseudomonas species by flux balance analysis: how good are genome-scale metabolic networks at predicting the differences?

To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

Genomer--a Swiss army knife for genome scaffolding

The increasing accessibility and reduced costs of sequencing has made genome analysis accessible to more and more researchers. Yet there remains a steep learning curve in the subsequent computational steps required to process raw reads into a database-deposited genome sequence. Here we describe “Genomer,” a tool to simplify the manual tasks of finishing and uploading a genome sequence to a database. Genomer can format a genome scaffold into the common files required for submission to GenBank. This software also simplifies updating a genome scaffold by allowing a human-readable YAML format file to be edited instead of large sequence files. Genomer is written as a command line tool and is an effort to make the manual process of genome scaffolding more robust and reproducible. Extensive documentation and video tutorials are available at http://next.gs.