Biology subjects

Heller, D.

Publications and source records attributed to Heller, D..

9 recordsLinked to original sources

bioRxiv2023

A genome-wide cytotoxicity screen of Cluster F1 mycobacteriophage Girr reveals novel inhibitors of Mycobacterium smegmatis growth

Over the past decade, thousands of bacteriophage genomes have been sequenced and annotated. A striking observation from this work is that known structural features and functions cannot be assigned for >65% of the encoded proteins. One approach to begin experimentally elucidating the function of these uncharacterized gene products is genome-wide screening to identify phage genes that confer phenotypes of interest like inhibition of host growth. This study describes the results of a screen evaluating the effects of overexpressing each gene encoded by the temperate Cluster F1 mycobacteriophage Girr on the growth of the host bacterium Mycobacterium smegmatis. Overexpression of 29 of the 102 Girr genes ([~]28% of the genome) resulted in mild to severe cytotoxicity. Of the 29 toxic genes described, 12 have no known function (NKF) and are predominately small proteins of <125 amino acids. Overexpression of the majority of these 12 cytotoxic NKF proteins resulted in moderate to severe growth reduction and represent novel antimicrobial products. The remaining 17 toxic genes have predicted functions, encoding products involved in phage structure, DNA replication/modification, DNA binding/gene regulation, or other enzymatic activity. Comparison of this dataset with prior genome-wide cytotoxicity screens of mycobacteriophages Waterfoul and Hammy reveals some common functional themes, though several of the predicted Girr functions associated with cytotoxicity in our report, including genes involved in lysogeny, have not been described previously. This study, completed as part of the HHMI-supported SEA-GENES project, highlights the power of parallel, genome-wide overexpression screens to identify novel interactions between phages and their hosts.

microbiology↗

bioRxiv2023

A genome-wide overexpression screen reveals Mycobacterium smegmatis growth inhibitors encoded by mycobacteriophage Hammy

During infection, bacteriophages produce diverse gene products to overcome bacterial anti-phage defenses, to outcompete other phages, and take over cellular processes. Even in the best-studied model phages, the roles of most phage-encoded gene products are unknown, and the phage population represents a largely untapped reservoir of novel gene functions. Considering the sheer size of this population, experimental screening methods are needed to sort through the enormous collection of available sequences and identify gene products that can modulate bacterial behavior for downstream functional characterization. Here, we describe the construction of a plasmid-based overexpression library of 94 genes encoded by Hammy, a Cluster K mycobacteriophage closely related to those infecting clinically important mycobacteria. The arrayed library was systematically screened in a plate-based cytotoxicity assay, identifying a diverse set of 24 gene products (representing 25% of the Hammy genome) capable of inhibiting growth of the host bacterium Mycobacterium smegmatis. Half of these are related to growth inhibitors previously identified in related phage Waterfoul, supporting their functional conservation; the other genes represent novel additions to the list of known anti-mycobacterial growth inhibitors. This work, conducted as part of the HHMI-supported Science Education Alliance Gene-function Elucidation by a Network of Emerging Scientists (SEA-GENES) project, highlights the value of parallel, comprehensive overexpression screens in exploring genome-wide patterns of phage gene function and novel interactions between phages and their hosts.

microbiology↗

bioRxiv2021

Single-cell sequencing unveils distinct immune microenvironment with CCR6-CCL20 crosstalk in human chronic pancreatitis

ObjectiveChronic pancreatitis (CP) is a potentially fatal disease of the exocrine pancreas, with no specific or effective approved therapies. Due to difficulty in accessing pancreas tissues, little is known about local immune responses or pathogenesis in human CP. We sought to characterize pancreas immune responses using tissues derived from patients with different etiologies of CP and non-CP organ donors in order to identify key signaling molecules associated with human CP. DesignWe performed single-cell level cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq) and T cell receptor sequencing of pancreatic immune cells isolated from organ donors, hereditary, and idiopathic CP patients who underwent total pancreatectomy. We validated gene expression data by performing flow cytometry and functional assay in the second CP patient cohort. ResultsDeep single-cell sequencing revealed distinct immune characteristics and significantly enriched CCR6+ CD4+ T cells in hereditary compared with idiopathic CP. In hereditary CP, a reduction in T cell clonality was observed due to the increased CD4+ T (Th) cells that replaced tissue-resident CD8+ T cells. Shared TCR clonotype analysis among T cell lineages also unveiled unique interactions between CCR6+ Th and Th1 subsets, and TCR clustering analysis showed unique common antigen binding motifs in hereditary CP. In addition, we observed a significant upregulation of the CCR6 ligand (CCL20) among monocytes in hereditary CP as compared with those in idiopathic CP. The functional significance of CCR6 expression in CD4+ T cells was confirmed by flow cytometry and chemotaxis assay. ConclusionSingle-cell sequencing with pancreatic immune cells in human CP highlights pancreas-specific immune crosstalk through the CCR6-CCL20 axis that might be leveraged as a potential future target in human hereditary CP. Significance of this studyO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIChronic pancreatitis (CP) is considered an irreversible fibroinflammatory pancreatic disease and remains a major source of morbidity among gastrointestinal diseases with no active approved therapy. C_LIO_LIInflammation is a known hallmark and contributor to CP pathogenesis. However, little is known about local immune responses in human CP especially with different etiologies. C_LI What are the new findings?O_LISingle-cell RNA sequencing of pancreatic immune cells from CP patients and organ donors revealed distinct immune transcriptomic features in CP versus non-diseased controls and hereditary versus idiopathic CP. C_LIO_LISingle-cell T cell receptor sequencing unveiled pancreas-specific clonal expansion in CD8+ T cells and CD4+ T cells-driven unique TCR repertoire changes in hereditary CP. C_LIO_LIWe identified that the CCR6-CCL20 axis was significantly upregulated in hereditary CP compared with controls or idiopathic CP suggesting a potential future target for human hereditary CP. C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe results of this study will improve our understanding of CP heterogeneity and identify distinct immune responses in different types of human CP that could provide novel conceptual directions for therapeutic strategies in treating hereditary and idiopathic CP. C_LIO_LIThe CCR6-CCL20 axis found in hereditary CP could be a potential novel targetable signaling pathways in the treatment of hereditary CP. C_LI

immunology↗

bioRxiv2020

SVIM-asm: Structural variant detection from haploid and diploid genome assemblies

MotivationWith the availability of new sequencing technologies, the generation of haplotype-resolved genome assemblies up to chromosome scale has become feasible. These assemblies capture the complete genetic information of both parental haplotypes, increase structural variant (SV) calling sensitivity and enable direct genotyping and phasing of SVs. Yet, existing SV callers are designed for haploid genome assemblies only, do not support genotyping or detect only a limited set of SV classes. ResultsWe introduce our method SVIM-asm for the detection and genotyping of six common classes of SVs from haploid and diploid genome assemblies. Compared against the only other existing SV caller for diploid assemblies, DipCall, SVIM-asm detects more SV classes and reached higher F1 scores for the detection of insertions and deletions on two recently published assemblies of the HG002 individual. Availability and ImplementationSVIM-asm has been implemented in Python and can be easily installed via bioconda. Its source code is available at github.com/eldariont/svim-asm. Contactvingron@molgen.mpg.de Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2020

SDip: A novel graph-based approach to haplotype-aware assembly based structural variant calling in targeted segmental duplications sequencing

Segmental duplications are important for understanding human diseases and evolution. The challenge to distinguish allelic and duplication sequences has hindered their phased assembly as well as characterization of structural variant calls. Here we have developed a novel graph-based approach that leverages single nucleotide differences in overlapping reads to distinguish allelic and duplication sequences information from long read accurate PacBio HiFi sequencing. These differences enable to generate allelic and duplication-specific overlaps in the graph to spell out phased assembly used for structural variant calling. We have applied our method to three public genomes: CHM13, NA12878 and HG002. Our method resolved 86% of duplicated regions fully with contig N50 up to 79 kb and produced <800 structural variant phased calls, outperforming state-of-the-part SDA method in terms of all metrics. Furthermore, we demonstrate the importance of phased assemblies and variant calls to the biologically-relevant duplicated genes such as SMN1, SRGAP2C, NPY4R and FAM72A. Our phased assemblies and accurate variant calling specifically in duplicated regions will enable the study of the evolution and adaptation of various species.

bioinformatics↗

bioRxiv2019

Efficient chromosome-scale haplotype-resolved assembly of human genomes

Haplotype-resolved or phased sequence assembly provides a complete picture of genomes and complex genetic variations. However, current phased assembly algorithms either fail to generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method that leverages long accurate reads and long-range conformation data for single individuals to generate chromosome-scale phased assembly within a day. Applied to three public human genomes, PGP1, HG002 and NA12878, our method produced haplotype-resolved assemblies with contig NG50 up to 25 Mb and phased [~]99.5% of heterozygous sites to 98-99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies to discover structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as HLA and KIR. Our improved method will enable high-quality precision medicine and facilitate new studies of individual haplotype variation and population diversity.

bioinformatics↗

bioRxiv2019

Genotyping structural variants in pangenome graphs using the vg toolkit

Structural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmarked vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

bioinformatics↗

bioRxiv2018

SVIM: Structural Variant Identification using Mapped Long Reads

MotivationStructural variants are defined as genomic variants larger than 50bp. They have been shown to affect more bases in any given genome than SNPs or small indels. Additionally, they have great impact on human phenotype and diversity and have been linked to numerous diseases. Due to their size and association with repeats, they are difficult to detect by shotgun sequencing, especially when based on short reads. Long read, single molecule sequencing technologies like those offered by Pacific Biosciences or Oxford Nanopore Technologies produce reads with a length of several thousand base pairs. Despite the higher error rate and sequencing cost, long read sequencing offers many advantages for the detection of structural variants. Yet, available software tools still do not fully exploit the possibilities.\n\nResultsWe present SVIM, a tool for the sensitive detection and precise characterization of structural variants from long read data. SVIM consists of three components for the collection, clustering and combination of structural variant signatures from read alignments. It discriminates five different variant classes including similar types, such as tandem and interspersed duplications and novel element insertions. SVIM is unique in its capability of extracting both the genomic origin and destination of duplications. It compares favorably with existing tools in evaluations on simulated data and real datasets from PacBio and Nanopore sequencing machines.\n\nAvailability and implementationThe source code and executables of SVIM are available on Github: github.com/eldariont/svim. SVIM has been implemented in Python 3 and published on bioconda and the Python Package Index.\n\nContactheller_d@molgen.mpg.de

bioinformatics↗

bioRxiv2018

Tree reconciliation combined with subsampling improves large scale inference of orthologous group hierarchies

BackgroundAn orthologous group (OG) comprises a set of orthologous and paralogous genes that share a last common ancestor (LCA). OGs are defined with respect to a chosen taxonomic level, which delimits the position of the LCA in time to a specified speciation event. A hierarchy of OGs expands on this notion, connecting more general OGs, distant in time, to more recent, fine-grained OGs, thereby spanning multiple levels of the tree of life. Large scale inference of OG hierarchies with independently computed taxonomic levels can suffer from inconsistencies between successive levels, such as the position in time of a duplication event. This can be due to confounding genetic signal or algorithmic limitations. Importantly, inconsistencies limit the potential use of OGs for functional annotation and third-party applications.\n\nResultsHere we present a new methodology to ensure hierarchical consistency of OGs across taxonomic levels. To resolve an inconsistency, we subsample the protein space of the OG members and perform gene tree-species tree reconciliation for each sampling. Differently from previous approaches, by subsampling the protein space, we avoid the notoriously diffcult task of accurately building and reconciling very large phylogenies. We implement the method into a high-throughput pipeline and apply it to the eggNOG database. We use independent protein domain definitions to validate its performance.\n\nConclusionThe presented consistency pipeline shows that, contrary to previous limitations, tree reconciliation can be a useful instrument for the construction of OG hierarchies. The key lies in the combination of sampling smaller trees and aggregating their reconciliations for robustness. Results show comparable or greater performance to previous pipelines. The code is available on Github at: https://github.com/meringlab/og_consistency_pipeline

bioinformatics↗