Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range. Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org.

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA—hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA’s bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies—BoxCar acquisition and trapped ion mobility spectrometry—both lead to deep and accurate proteome quantification.

Summary Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated ‘prophage genome maps’ and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. Availability and implementation Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. Supplementary information Supplementary data are available at Bioinformatics online.

The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

AbstractSummaryPhigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It provides putative taxonomic annotations that can distinguish tailed from non-tailed phages. It is applicable for mining prophage regions from large metagenomic datasets.AvailabilitySource code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.