Biology subjects

Janssen, S.

Publications and source records attributed to Janssen, S..

14 recordsLinked to original sources

bioRxiv2026

Evaluation of object detection neural networks to find topologically associated domains in bulk Hi-C data

Topologically associated domains (TADs) shape the three-dimensional structure of chromatin and contribute to gene regulation by arranging regulatory elements and genes in spatial proximity. This spatial proximity is captured by Hi-C, an experimental method, which quantifies contact frequencies between all pairs of genomic loci. In bulk Hi-C data, TADs can be found in the form of gapped, nested and partially overlapping squares centered on the main diagonal of the Hi-C matrix. We shift the problem of TAD identification into the domain of computer vision by detecting TADs in Hi-C in the form of squares in images. For this we use object detection, which aims to classify object instances in images. This study evaluates the applicability of the object detection neural networks YOLOv8 and Mask R-CNN on the identification of TADs in bulk Hi-C data. We build image-like data from Hi-C matrices, predict reference TADs with a state-of-the-art TAD caller, train the models and evaluate the detections. Our results confirm that YOLOv8 and Mask R-CNN learn to detect reference TADs, new TADs and overlapping TADs (although absent in training data). All three show increased ChIP-Seq signal of the TAD-associated factors CTCF, RAD21 and H3K4me3 on their boundaries, emphasizing their biological reliability. Comparisons with reference TADs indicate that Mask R-CNN detects more TADs with less precise positioning, while YOLOv8 detects fewer TADs with lower nesting complexity but improved positioning.

bioinformatics↗

bioRxiv2026

Intra-individual variation in leaf microbiota matches within-crown environmental heterogeneity and promotes tree performance

Plant-associated microbial communities exhibit pronounced specificity across biological and spatial scales. While the patterns and accompanied functions have been well documented across and within plant species, the functional importance of intra-individual variation remains underexplored. Particularly in trees that experience strong environmental gradients within single crowns, stratum-specific microbiota may significantly contribute to plant performance. We experimentally tested whether variation in microbiota within the crown of Quercus robur is related to host performance. In mesocosm experiments, we transferred microbial communities derived from sun and shade leaves to germ-reduced clonal individuals of the same species and applied UV radiation simulating conditions that matched or mismatched the origin of the microbial inoculum (environmental matching). Our results demonstrate that matching microbiota-environment combinations increased plant performance compared to mismatching combinations. We infer that pronounced intra-individual variation of leaf-associated microbial communities not only reflects environmental heterogeneity along canopy strata but is functionally relevant for the plant host.

ecology↗

bioRxiv2026

Activity of a three-phage combination against Mycobacterium tuberculosis in disease-relevant conditions

Phage therapy offers promise to combat antimicrobial resistance, including drug-resistant tuberculosis (TB). Understanding phage activity against Mycobacterium tuberculosis (Mtb) adapted to physiologic microenvironments, such as hypoxia and acidity in granulomas, is essential since these conditions induce non-replicating states. We evaluated a phage combination against Mtb under hypoxic, acidic (pH 5.5), and stationary-phase conditions in vitro. In planktonic Mtb growth conditions, phage concentrations increased around day seven followed by a significant reduction in Mtb H37Rv load, which was maintained over 31 days. Phage addition prevented regrowth was observed with rifampicin and isoniazid alone. Individual phage stability was differentially affected by acidic media conditions, resulting in variability of antimycobacterial activity. In hypoxic conditions and stationary growth experiments, phage titers remained stable over time with no change in mycobacterial load compared to controls. Model-based predictions were able to adequately capture phage-mycobacterial interactions with and without rifampicin. The lack of antimycobacterial activity in assays with non-replicating mycobacteria suggest that phages need actively replicating mycobacteria to exert lytic activity. Stable phage concentrations in assays with non-replicating mycobacteria suggests low grade phage replication in these conditions. Established models can support future study design through simulations of different experimental scenarios.

microbiology↗

bioRxiv2024

FLASH Bragg-peak irradiation with a therapeutic carbon ion beam: first in vivo results

Background and purposeIn recent years, ultra-high dose rate (UHDR) irradiation has emerged as a promising innovative approach to cancer treatment. Characteristic feature of this regimen, commonly referred to as FLASH effect, demonstrated primarily for electrons, photons or protons, is the improved normal tissue sparing, while the tumor control is similar to the one of the conventional dose-rate (CDR) treatments. The FLASH mechanism is, however, unknown. One major question is whether this effect is maintained when using densely ionizing (high-LET) heavy nuclei. Materials and MethodsHere we report the effects of 20 Gy UHDR heavy ion irradiation in clinically relevant conditions, i.e., at high-LET in the spread-out Bragg peak (SOBP) of a 12C beam using an osteosarcoma mouse model. ResultsWe show that UHDR irradiation was less toxic in the normal tissue compared to CDR while maintaining tumor control. The immune activation was also comparable in UHDR and CDR groups. We observed that the gut microbiome was altered in mice injected with the tumor compared to healthy animals, but both UHDR and CDR exposures steered the metagenome toward a balanced state. ConclusionsThe results show that the FLASH effect is safe and effective in heavy ion therapy and provide an important benchmark for the current mechanistic FLASH models. Highlights- FLASH irradiation with SOBP carbon ions spares normal tissue in mouse - Tumor control, immune response, and gut microbioma changes are induced at the same extent both at conventional and ultra-high dose rate - FLASH carbon ion irradiation is a safe and effective alternative to conventional radiotherapy.

cancer biology↗

bioRxiv2024

The host genotype actively shapes its microbiome across generations

BackgroundThe microbiome greatly affects health and wellbeing. Evolutionarily, it is doubtful that a host would rely on chance alone to pass on microbial colonization to its offspring. However, the literature currently offers only limited evidence regarding two alternative hypotheses: active microbial shaping by host genetic factors or transmission of a microbial maternal legacy. ResultsTo further dissect the influence of host genetics and maternal inheritance, we collected 2-cell stage embryos from two representative wildtypes, C57BL6/J and BALB/c, and transferred a mixture of both genotype embryos into hybrid recipient mice to be inoculated by an identical microbiome at birth. ConclusionsObserving the offspring for six generations unequivocally emphasizes the impact of host genetic factors over maternal legacy in constant environments, akin to murine laboratory experiments. Interestingly, maternal legacy solely controlled the microbiome in the first offspring generation. However, current evidence supporting maternal legacy has not extended beyond this initial generation, resolving the aforementioned debate. O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/584950v2_ufig1.gif" ALT="Figure 5"> View larger version (48K): org.highwire.dtl.DTLVardef@790822org.highwire.dtl.DTLVardef@4f486org.highwire.dtl.DTLVardef@151ab46org.highwire.dtl.DTLVardef@c3ab66_HPS_FORMAT_FIGEXP M_FIG graphical abstract C_FIG

ecology↗

bioRxiv2023

Time-Informed Dimensionality Reduction for Longitudinal Microbiome Studies

Longitudinal studies are crucial for understanding complex microbiome dynamics and their link to health. We introduce TEMPoral TEnsor Decomposition (TEMPTED), a time-informed dimensionality reduction method for high-dimensional longitudinal data that treats time as a continuous variable, effectively characterizing temporal information and handling varying temporal sampling. TEMPTED captures key microbial dynamics, facilitates beta-diversity analysis, and enhances reproducibility by transferring learned representations to new data. In simulations, it achieves 90% accuracy in phenotype classification, significantly outperforming existing methods. In real data, TEMPTED identifies vaginal microbial markers linked to term and preterm births, demonstrating robust performance across datasets and sequencing platforms.

bioinformatics↗

bioRxiv2023

Reply to: Caution Regarding the Specificities of Pan-Cancer Microbial Structure

The cancer microbiome field tremendously accelerated following the release of our manuscript nearly three years ago1, including direct validation of our cancer type-specific conclusions in independent, international cohorts2,3 and the tumor microbiomes adoption into the hallmarks of cancer4. Disentangling contamination signals from biological signals is an important consideration for this research field. Therefore, despite numerous, high-impact, peer-reviewed research papers that either validated our conclusions or extended them using data we released2,5-13, we carefully considered criticism raised by Gihawi et al. about potential mishandling of contaminants, batch effects, and machine learning approaches--all of which were central topics in our manuscript. Nonetheless, a close examination of each concern alongside the original manuscript and re-analyses of our published data strongly demonstrates the robustness of the original findings. To remove all doubt, however, we have reproduced all key conclusions from the original manuscript using only overlapping bacterial genera identified in a highly decontaminated, multi-cancer, international cohort (Weizmann Institute of Science, WIS)2, with or without batch correction, and with multiclass machine learning analyses to mitigate class imbalances. Our published pan-cancer mycobiome manuscript3 also affirms these findings using updated, state-of-the-art methods. We also note that every analysis shown here was possible using public data and code that we had already provided.

bioinformatics↗

bioRxiv2022

Sequence-structure-function relationships in the microbial protein universe

Abstract / SummaryFor the past half-century, structural biologists relied on the notion that similar protein sequences give rise to similar structures and functions. While this assumption has driven research to explore certain parts of the protein universe, it disregards spaces that dont rely on this assumption. Here we explore areas of the protein universe where similar protein functions can be achieved by different sequences and different structures. We predict [~]200,000 structures for diverse protein sequences from 1,003 representative genomes1 across the microbial tree of life, and annotate them functionally on a per-residue basis. Structure prediction is accomplished using the World Community Grid, a large-scale citizen science initiative. The resulting database of structural models is complementary to the AlphaFold database, with regards to domains of life as well as sequence diversity and sequence length. We identify 148 novel folds and describe examples where we map specific functions to structural motifs. We also show that the structural space is continuous and largely saturated, highlighting the need for shifting the focus from obtaining structures to putting them into context, to transform all branches of biology, including a shift from sequence-based to sequence-structure-function based meta-omics analyses.

bioinformatics↗

bioRxiv2022

ATAC-Seq and RNA-Seq combined analysis elucidates the impact of BORIS/CTCFL on melanoma progression, mediated by chromatin accessibility and gene expression alterations

Melanoma is the deadliest form of skin cancer, due to its tendency to metastasize early. Brother of Regulator of Imprinted Sites (BORIS), also known as CCCTC binding factor-Like (CTCFL), is a transcription regulator that becomes ectopically expressed in melanoma. We recently showed that BORIS contributes to melanoma phenotype switching by altering the gene expression program of proliferative melanoma cells in favor of a more invasive phenotype. However, how BORIS alters the transcriptome remains unclear. Here, ATAC-seq was used to study BORIS-mediated chromatin accessibility alterations in proliferative melanoma cells. Genes that gained promoter accessibility following ectopic BORIS expression, were enriched for melanoma-specific invasive genes as well as invasion-associated biological processes, while promoters of genes associated with proliferation show reduce accessibility. Integration of ATAC-Seq and RNA-Seq data demonstrates that increased chromatin accessibility is associated with transcriptional upregulation of genes involved in tumor progression processes, and the aberrant activation of oncogenic transcription factors, while reduced chromatin accessibility and downregulated genes, were associated with repressed activity of tumor suppressors. Together, these findings indicate that BORIS mediates transcriptional reprogramming in melanoma cells by altering chromatin accessibility and gene expression, shifting the cellular transcription landscape of proliferative melanoma cells towards a pro-invasive genetic signature. SignificanceWe recently reported that BORIS contributes to melanoma phenotype switching by altering the transcriptional landscape of melanoma cells from a proliferative to an invasive state. In this study, using ATAC-Seq, we demonstrate that ectopic BORIS expression in proliferative melanoma cells leads to increased chromatin accessibility at promoters of upregulated invasion-associated genes. Importantly, by integrating the ATAC-Seq data with RNA-Seq data, we were able to identify key cancer-associated transcription factors that become aberrantly activated or repressed following ectopic BORIS expression. Taken together, this study sheds light on the mechanisms by which BORIS mediates phenotype switching in melanoma cells.

cancer biology↗

bioRxiv2021

SARS-CoV-2 binding and neutralizing antibody levels after vaccination with Ad26.COV2.S predict durable protection in rhesus macaques

The first COVID-19 vaccines have recently gained authorization for emergency use.1,2 At this moment, limited knowledge on duration of immunity and efficacy of these vaccines is available. Data on other coronaviruses after natural infection suggest that immunity to SARS-CoV-2 might be short lived,3,4 and preliminary evidence indicates waning antibody titers following SARS-CoV-2 infection.5 Here we model the relationship between immunogenicity and protective efficacy of a series of Ad26 vectors encoding stabilized variants of the SARS-CoV-2 Spike (S) protein in rhesus macaques6,7,8 and validate the analyses by challenging macaques 6 months after immunization with the Ad26.COV2.S vaccine candidate that has been selected for clinical development. We find that Ad26.COV2.S confers durable protection against replication of SARS-CoV-2 in the lungs that is predicted by the levels of S-binding and neutralizing antibodies. These results suggest that Ad26.COV2.S could confer durable protection in humans and that immunological correlates of protection may enable the prediction of durability of protection.

immunology↗

bioRxiv2020

EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive tool for visualizing trees in the context of microbiome, metabolome, etc. community data scalable beyond modern large datasets like the Earth Microbiome Project. EMPress provides novel functionality--including ordination integration and animations--alongside many standard tree visualization features, and thus simplifies exploratory analyses of many forms of omic data.

bioinformatics↗

bioRxiv2018

Assessing taxonomic metagenome profilers with OPAL

Taxonomic metagenome profilers predict the presence and relative abundance of microorganisms from shotgun sequence samples of DNA isolated directly from a microbial community. Over the past years, there has been an explosive growth of software and algorithms for this task, resulting in a need for more systematic comparisons of these methods based on relevant performance criteria. Here, we present OPAL, a software package implementing commonly used performance metrics, including those of the first challenge of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI), together with convenient visualizations. In addition, OPAL implements diversity metrics from microbial ecology, as well as run time and memory efficiency measurements. By allowing users to customize the relative importance of metrics, OPAL facilitates in-depth performance comparisons, as well as the development of new methods and data analysis workflows. To demonstrate the application, we compared seven profilers on benchmark datasets of the first and second CAMI challenges using all metrics and performance measurements available in OPAL. The software is implemented in Python 3 and available under the Apache 2.0 license on GitHub (https://github.com/CAMI-challenge/OPAL).\n\nAuthor summaryThere are many computational approaches for inferring the presence and relative abundance of taxa (i.e. taxonomic profiling) from shotgun metagenome samples of microbial communities, making systematic performance evaluations a very important task. However, there has yet to be introduced a computational framework in which profiler performances can be compared. This delays method development and applied studies, as researchers need to implement their own custom evaluation frameworks. Here, we present OPAL, a software package that facilitates standardized comparisons of taxonomic metagenome profilers. It implements a variety of performance metrics frequently employed in microbiome research, including runtime and memory usage, and generates comparison reports and visualizations. OPAL thus facilitates and accelerates benchmarking of taxonomic profiling techniques on ground truth data. This enables researchers to arrive at informed decisions about which computational techniques to use for specific datasets and research questions.

bioinformatics↗

bioRxiv2018

American Gut: an Open Platform for Citizen-Science Microbiome Research

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the USA, UK, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes as compared to environmental samples, demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations, uncover new molecules and kinds of molecular communities in the human stool metabolome, and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness, and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.\n\nImportanceWe show that a citizen-science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n=1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet which we confirm with untargeted metabolomics on hundreds of samples.

microbiology↗

bioRxiv2017

Critical Assessment of Metagenome Interpretation - a benchmark of computational metagenomics software

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

bioinformatics↗