Empowering bioinformatics communities with Nextflow and nf-core.

Standardized analysis pipelines contribute to making data bioinformatics research compliant with the paradigm of Findability, Accessibility, Interoperability, and Reusability (FAIR), and facilitate collaboration. Nextflow and Snakemake, two popular command-line solutions, are increasingly adopted by users, complementing GUI-based platforms such as Galaxy. We report recent developments of the nf-core framework with the new Nextflow Domain-Specific Language (DSL2).

AMULETY: A Python package to embed adaptive immune receptor sequences.

Large language models have been developed to capture relevant features of adaptive immune receptors, each with unique potential applications. However, the diversity in available models presents challenges in accessibility and usability for downstream applications. Here we present AMULETY (Adaptive imMUne receptor Language model Embedding Tool), a Python-based software package to generate language model embeddings for adaptive immune receptor sequences, enabling users to leverage the strengths of different models without the need for complex configuration.

A single-cell atlas of circulating immune cells over the first 2 months of age in extremely premature infants.

Extremely premature infants (EPIs) who are born before 30 weeks of gestation are susceptible to infection; however, the trajectory of their peripheral immunity is poorly understood. Here, we undertook longitudinal analyses of immune cells from 250 μl of whole blood at 1 week, 1 month, and 2 months from 10 EPIs and compared these with samples from healthy adults and with preterm and full-term cord blood samples. Single-cell suspensions from individual samples were split to perform single-cell RNA sequencing, T and B cell receptor sequencing, and phosphoprotein mass cytometry.

Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors.

The post-acute sequelae of SARS-CoV-2 (PASC), also known as long COVID, remain a significant health issue that is incompletely understood. Predicting which acutely infected individuals will go on to develop long COVID is challenging due to the lack of established biomarkers, clear disease mechanisms, or well-defined sub-phenotypes. Machine learning (ML) models offer the potential to address this by leveraging clinical data to enhance diagnostic precision.

Identification of a multi-omics factor predictive of long COVID in the IMPACC study.

Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which often debilitating symptoms persist for at least three months. Elucidating the biologic underpinnings of LC could identify therapeutic opportunities. We utilized machine learning methods on biologic analytes and patient reported outcome surveys provided over 12 months after hospital discharge from >500 hospitalized COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor".

Nf-Root: A Best-Practice Pipeline for Deep-Learning-Based Analysis of Apoplastic pH in Microscopy Images of Developmental Zones in Plant Root Tissue.

Hormonal mechanisms associated with cell elongation play a vital role in the development and growth of plants. Here, we report Nextflow-root (nf-root), a novel best-practice pipeline for deep-learning-based analysis of fluorescence microscopy images of plant root tissue from A. thaliana.

RAGE is a key regulator of ductular reaction-mediated fibrosis during cholestasis.

Ductular reaction (DR) is the hallmark of cholestatic diseases manifested in the proliferation of bile ductules lined by biliary epithelial cells (BECs). It is commonly associated with an increased risk of fibrosis and liver failure. The receptor for advanced glycation end products (RAGE) was identified as a critical mediator of DR during chronic injury.

In-depth analysis of serum antibodies against Epstein-Barr virus lifecycle proteins, and EBNA1, ANO2, GlialCAM and CRYAB peptides in patients with multiple sclerosis.

Background: A strong association between multiple sclerosis (MS) and Epstein-Barr virus (EBV) has been established but the exact role of EBV in MS remains controversial. Recently, molecular mimicry between EBNA1 and specific GlialCAM, CRYAB and ANO2 peptides has been suggested as a possible pathophysiological mechanism. The aim of this study was to analyse anti-EBV antibodies in MS patients against (I) EBV lifecycle proteins, (II) putative cross-reactive peptides, and (III) during treatment.

NCBench: providing an open, reproducible, transparent, adaptable, and continuous benchmark approach for DNA-sequencing-based variant calling.

We present the results of the human genomic small variant calling benchmarking initiative of the German Research Foundation (DFG) funded Next Generation Sequencing Competence Network (NGS-CN) and the German Human Genome-Phenome Archive (GHGA). In this effort, we developed NCBench, a continuous benchmarking platform for the evaluation of small genomic variant callsets in terms of recall, precision, and false positive/negative error patterns. NCBench is implemented as a continuously re-evaluated open-source repository.

nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures.

PI3Kγ in B cells promotes antibody responses and generation of antibody-secreting cells.

The differentiation of naive and memory B cells into antibody-secreting cells (ASCs) is a key feature of adaptive immunity. The requirement for phosphoinositide 3-kinase-delta (PI3Kδ) to support B cell biology has been investigated intensively; however, specific functions of the related phosphoinositide 3-kinase-gamma (PI3Kγ) complex in B lineage cells have not. In the present study, we report that PI3Kγ promotes robust antibody responses induced by T cell-dependent antigens.

Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery.

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples.

How tool combinations in different pipeline versions affect the outcome in RNA-seq analysis.

Data analysis tools are continuously changed and improved over time. In order to test how these changes influence the comparability between analyses, the output of different workflow options of the nf-core/rnaseq pipeline were compared. Five different pipeline settings (STAR+Salmon, STAR+RSEM, STAR+featureCounts, HISAT2+featureCounts, pseudoaligner Salmon) were run on three datasets (human, Arabidopsis, zebrafish) containing spike-ins of the External RNA Control Consortium (ERCC).

nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures.

Cladribine treatment specifically affects peripheral blood memory B cell clones and clonal expansion in multiple sclerosis patients.

Introduction: B cells are acknowledged as crucial players in the pathogenesis of multiple sclerosis (MS). Several disease modifying drugs including cladribine have been shown to exert differential effects on peripheral blood B cell subsets. However, little is known regarding functional changes within the peripheral B cell populations.

Clinical outcome of biomarker-guided therapies in adult patients with tumors of the nervous system.

Background: The clinical utility of molecular profiling and targeted therapies for neuro-oncology patients outside of clinical trials is not established. We aimed at investigating feasibility and clinical utility of molecular profiling and targeted therapy in adult patients with advanced tumors in the nervous system within a prospective observational study.

Methods: molecular tumor board (MTB)@ZPM (NCT03503149) is a prospective observational precision medicine study for patients with advanced tumors.

A data management infrastructure for the integration of imaging and omics data in life sciences.

Background: As technical developments in omics and biomedical imaging increase the throughput of data generation in life sciences, the need for information systems capable of managing heterogeneous digital assets is increasing. In particular, systems supporting the findability, accessibility, interoperability, and reusability (FAIR) principles of scientific data management.

Results: We propose a Service Oriented Architecture approach for integrated management and analysis of multi-omics and biomedical imaging data.

nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning.

The analysis of shotgun metagenomic data provides valuable insights into microbial communities, while allowing resolution at individual genome level. In absence of complete reference genomes, this requires the reconstruction of metagenome assembled genomes (MAGs) from sequencing reads. We present the nf-core/mag pipeline for metagenome assembly, binning and taxonomic classification.

Next Generation Sequencing of Cerebrospinal Fluid B Cell Repertoires in Multiple Sclerosis and Other Neuro-Inflammatory Diseases-A Comprehensive Review.

During the last few decades, the role of B cells has been well established and redefined in neuro-inflammatory diseases, including multiple sclerosis and autoantibody-associated diseases. In particular, B cell maturation and trafficking across the blood-brain barrier (BBB) has recently been deciphered with the development of next-generation sequencing (NGS) approaches, which allow the assessment of representative cerebrospinal fluid (CSF) and peripheral blood B cell repertoires. In this review, we perform literature research focusing on NGS studies that allow further insights into B cell pathophysiology during neuro-inflammation.

Specific Induction of Double Negative B Cells During Protective and Pathogenic Immune Responses.

Double negative (DN) (CD19CD20CD27IgD) B cells are expanded in patients with autoimmune and infectious diseases; however their role in the humoral immune response remains unclear. Using systematic flow cytometric analyses of peripheral blood B cell subsets, we observed an inflated DN B cell population in patients with variety of active inflammatory conditions: myasthenia gravis, Guillain-Barré syndrome, neuromyelitis optica spectrum disorder, meningitis/encephalitis, and rheumatic disorders. Furthermore, we were able to induce DN B cells in healthy subjects following vaccination against influenza and tick borne encephalitis virus.

Clinical and Genetic Tumor Characteristics of Responding and Non-Responding Patients to PD-1 Inhibition in Hepatocellular Carcinoma.

Immune checkpoint inhibitors (ICIs) belong to the therapeutic armamentarium in advanced hepatocellular carcinoma (HCC). However, only a minority of patients benefit from immunotherapy. Therefore, we aimed to identify indicators of therapy response.

Morphing of Amphipathic Helices to Explore the Activity and Selectivity of Membranolytic Antimicrobial Peptides.

Naturally occurring membranolytic antimicrobial peptides (AMPs) are rarely cell-type selective and highly potent at the same time. Template-based peptide design can be used to generate AMPs with improved properties . Following this approach, 18 linear peptides were obtained by computationally morphing the natural AMP Aurein 2.

In silico design and optimization of selective membranolytic anticancer peptides.

Membranolytic anticancer peptides represent a potential strategy in the fight against cancer. However, our understanding of the underlying structure-activity relationships and the mechanisms driving their cell selectivity is still limited. We developed a computational approach as a step towards the rational design of potent and selective anticancer peptides.