NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface.

Background: Vaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens genome or proteome through computational analyses. When NERVE (New Enhanced RV Environment), the first RV software integrating tools to perform the selection of VCs, was released, it prompted further development in the field. However, the problem-solving potential of most, if not all, RV programs is still largely unexploited by experimental vaccinologists that impaired by somehow difficult interfaces, requiring bioinformatic skills.

Phosphorylation in the Proteome: A Meta-Analysis of Publicly Available Data Sets.

Malaria is a deadly disease caused by Apicomplexan parasites of the genus. Several species of the genus are known to be infectious to humans, of which is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signaling and hence regulate many biological processes in homeostasis and host infection, of which the most highly studied is phosphorylation.

Base editing screens define the genetic landscape of cancer drug resistance mechanisms.

Drug resistance is a principal limitation to the long-term efficacy of cancer therapies. Cancer genome sequencing can retrospectively delineate the genetic basis of drug resistance, but this requires large numbers of post-treatment samples to nominate causal variants. Here we prospectively identify genetic mechanisms of resistance to ten oncology drugs from CRISPR base editing mutagenesis screens in four cancer cell lines using a guide RNA library predicted to install 32,476 variants in 11 cancer genes.

Genomic epidemiology and longitudinal sampling of ward wastewater environments and patients reveals complexity of the transmission dynamics of -carbapenemase-producing Enterobacterales in a hospital setting.

Background: Healthcare-associated wastewater and asymptomatic patient reservoirs colonized by carbapenemase-producing Enterobacterales (CPE) contribute to nosocomial CPE dissemination, but the characteristics and dynamics of this remain unclear.

Methods: We systematically sampled wastewater sites ( = 4488 samples; 349 sites) and patients ( = 1247) across six wards over 6-12 months to understand bla-associated CPE (KPC-E) diversity within these reservoirs and transmission in a healthcare setting. Up to five KPC-E-positive isolates per sample were sequenced (Illumina).

The evolution of computational research in a data-centric world.

Computational data-centric research techniques play a prevalent and multi-disciplinary role in life science research. In the past, scientists in wet labs generated the data, and computational researchers focused on creating tools for the analysis of those data. Computational researchers are now becoming more independent and taking leadership roles within biomedical projects, leveraging the increased availability of public data.

COPO - Managing sample metadata for biodiversity: considerations from the Darwin Tree of Life project.

Large-scale reference genome sequencing projects for all of biodiversity are underway and common standards have been in place for some years to enable the understanding and sharing of sequence data. However, the metadata that describes the collection, processing and management of samples, and link to the associated sequencing and genome data, are not yet adequately developed and standardised for these projects. At the time of writing, the Darwin Tree of Life (DToL) Project is over two years into its ten-year ambition to sequence all described eukaryotic species in Britain and Ireland.

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions.

From the catalytic breakdown of nutrients to signaling, interactions between metabolites and proteins play an essential role in cellular function. An important case is cell-cell communication, where metabolites, secreted into the microenvironment, initiate signaling cascades by binding to intra- or extracellular receptors of neighboring cells. Protein-protein cell-cell communication interactions are routinely predicted from transcriptomic data.

Communicating Mass Spectrometry Quality Information in mzQC with Python, R, and Java.

Mass spectrometry is a powerful technique for analyzing molecules in complex biological samples. However, inter- and intralaboratory variability and bias can affect the data due to various factors, including sample handling and preparation, instrument calibration and performance, and data acquisition and processing. To address this issue, the Quality Control (QC) working group of the Human Proteome Organization's Proteomics Standards Initiative has established the standard mzQC file format for reporting and exchanging information relating to data quality.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins.

A single-cell atlas enables mapping of homeostatic cellular shifts in the adult human breast.

Here we use single-cell RNA sequencing to compile a human breast cell atlas assembled from 55 donors that had undergone reduction mammoplasties or risk reduction mastectomies. From more than 800,000 cells we identified 41 cell subclusters across the epithelial, immune and stromal compartments. The contribution of these different clusters varied according to the natural history of the tissue.

scSNV-seq: high-throughput phenotyping of single nucleotide variants by coupled single-cell genotyping and transcriptomics.

CRISPR screens with single-cell transcriptomic readouts are a valuable tool to understand the effect of genetic perturbations including single nucleotide variants (SNVs) associated with diseases. Interpretation of these data is currently limited as genotypes cannot be accurately inferred from guide RNA identity alone. scSNV-seq overcomes this limitation by coupling single-cell genotyping and transcriptomics of the same cells enabling accurate and high-throughput screening of SNVs.

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins.

Targeting oncogenic microRNAs from the miR-371~373 and miR-302/367 clusters in malignant germ cell tumours causes growth inhibition through cell cycle disruption.

Background: MiR-371~373 and miR-302/367 cluster over-expression occurs in all malignant germ cell tumours (GCTs), regardless of age (paediatric/adult), site (gonadal/extragonadal), or subtype [seminoma, yolk sac tumour (YST), embryonal carcinoma (EC)]. Six of eight microRNAs from these clusters contain the seed sequence 'AAGUGC', determining mRNA targeting. Here we sought to identify the significance of these observations by targeting these microRNAs functionally.

TopDownApp: An open and modular platform for analysis and visualisation of top-down proteomics data.

Although Top-down (TD) proteomics techniques, aimed at the analysis of intact proteins and proteoforms, are becoming increasingly popular, efforts are needed at different levels to generalise their adoption. In this context, there are numerous improvements that are possible in the area of open science practices, including a greater application of the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. These include, for example, increased data sharing practices and readily available open data standards.

Highlights from the 1st European cancer dependency map symposium and workshop.

The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap.

Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature.

Background: To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections.

Methods: Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138).

Base editing screens map mutations affecting interferon-γ signaling in cancer.

Interferon-γ (IFN-γ) signaling mediates host responses to infection, inflammation and anti-tumor immunity. Mutations in the IFN-γ signaling pathway cause immunological disorders, hematological malignancies, and resistance to immune checkpoint blockade (ICB) in cancer; however, the function of most clinically observed variants remains unknown. Here, we systematically investigate the genetic determinants of IFN-γ response in colorectal cancer cells using CRISPR-Cas9 screens and base editing mutagenesis.

Clonal transcriptomics identifies mechanisms of chemoresistance and empowers rational design of combination therapies.

Tumour heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here, we utilise clonal transcriptomics with WILD-seq; holistic nterrogation of ineage ynamics by uencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy.

Is DIA proteomics data FAIR? Current data sharing practices, available bioinformatics infrastructure and recommendations for the future.

Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in, for example, instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards since public databases and data standards for proteomics were mostly designed with DDA data in mind.

Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas.

The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource.