Biology subjects

Ruff, S.

Publications and source records attributed to Ruff, S..

5 recordsLinked to original sources

bioRxiv2026

Data-Driven Virus Discovery with Virushunter and Virusgatherer

We present Virushunter and Virusgatherer, a bipartite computational workflow for discovering viral genomes from unprocessed next-generation sequencing data. Virushunter conducts a profile Hidden Markov Model-based sequence homology search for viral hallmark protein-coding sequence reads to construct microcontigs, which are used as seeds for targeted viral genome assembly by Virusgatherer. We showcase the application of Virushunter and Virusgatherer through an RNA virus-wide screen in 3348 bat transcriptome sequencing experiments from the Sequence Read Archive. Many of the discovered viruses are likely prototypes of new putative virus species, including a novel alphacoronavirus identified in a South American velvety free-tailed bat and a novel rhabdovirus in a European barbastelle bat. The tools are implemented as a reproducible Snakemake pipeline, which is available at https://github.com/lauberlab/VirusHunterGatherer.

bioinformatics↗

bioRxiv2025

Maternal Influenza A Virus Infection Induces Antiviral and Immune Dysregulation in the Placenta and Fetus Without Vertical Transmission

Influenza A virus (IAV) infection during pregnancy is associated with stillbirth and preterm birth, but the degree to which IAV alters placental and fetal immunity is poorly understood. The objective of our study was to determine the immunologic impact of maternal IAV infection on the placenta and fetus in a pigtail macaque (Macaca nemestrina) model. Pregnant pigtail macaques were inoculated with 107 plaque forming units (PFU) of IAV [A/California/07/2009 (H1N1)] and underwent necropsy 5 days post-infection (N=11). Results were compared to uninfected historical controls (N=16). IAV inoculation induced maternal pneumonia in all cases. Stillbirth occurred in 18% (2/11) of IAV-infected pregnancies, but not in controls. While vertical transmission was not observed, low-level IAV viral RNA was detected in two placentas. In the placenta, maternal IAV infection was associated with increased IL-1{beta}, IL-18, and IFN-{beta} levels, and an upregulated type I interferon (IFN) transcriptional response. IAV infection was also associated with significantly higher frequencies of intermediate and non-classical monocytes, plasmacytoid dendritic cells, CD4 T cells, and NKT cells in the fetus (lung, lymph node, blood). Although placental immune and transcriptional perturbations were rarely correlated with maternal IAV disease indicators (e.g., maternal lung viral load/IFN-/IFN-{beta}/IL-6), there were consistent and significant correlations between these metrics and perturbed immune cell populations in the fetus (CD4+ and CD8+ T cells, plasmacytoid dendritic cells, monocyte sub-populations). Maternal IAV infection disrupted both placental and fetal immune environments, but only fetal immune alterations correlated with maternal lung disease severity. One Sentence SummaryMaternal influenza A virus infection in pregnant pigtail macaques dysregulates placental and fetal immunity, with disease severity correlating strongly with fetal, but not placental, immune perturbations.

systems biology↗

bioRxiv2025

scTrimClust: A Fast Approach to Robust scRNA-seq Analysis Using Trimmed Cell Clusters

Detection of marker genes and other data analyses in single cell RNA-sequencing (scRNA-seq) experiments very much rely on the result of unsupervised clustering of cells. However, in 2-dimensional representation of clustering results, several cells appear as outliers or in the border area of a cluster suggesting that these cells may not adequately represent a particular cell type. We propose a novel and fast approach, scTrimClust, for identifying cells that may be interpreted of extreme specimens of their cell type. Identification is based on concave hulls build around each 2-dimensional cell cluster and the distance of each cell to the border area of its population. We study in two data examples, how cells with non-representative expression profile can influence the results of the analysis. We found that some sets of marker genes are little influenced by extreme cells while other sets are strongly modified, and must therefore be treated carefully. scTrimClust is also useful to compare the influence of other parameters of an scRNA-seq analysis, e.g. normalization or the clustering approach, on the results. We also provide a software implementation of scTrimClust.

bioinformatics↗

bioRxiv2020

Identification of PIM1 substrates reveals a role for NDRG1 in prostate cancer cellular migration and invasion

PIM1 is an oncogenic serine/threonine kinase that promotes and maintains prostate tumorigenesis. To more fully understand the mechanism by which PIM1 promotes oncogenesis, we performed a chemical genetic screen to identify direct PIM1 substrates in prostate cancer cells. The PIM1 substrates we identified were involved in a variety of oncogenic processes, and included N-Myc Downstream-Regulated Gene 1 (NDRG1), which has reported roles in the suppression of cancer cell invasion and metastasis. NDRG1 is phosphorylated by PIM1 at serine 330 (pS330), and the level of NDRG1 pS330 is associated with high grade compared to low grade prostate tumors. While NDRG1 pS330 is largely cytoplasmic, total NDRG1 is both cytoplasmic and nuclear. Mechanistically, PIM1 phosphorylation of NDRG1 decreases its stability, reducing its interaction with AR, and thereby lowering expression of AR target genes. PIM1-dependent NDRG1 phosphorylation also reduces NDRG1s ability to suppress prostate cancer cell migration and invasion. Our study identifies a novel set of PIM1 substrates in prostate cancer cells using a direct, unbiased chemical genetic screen. It also provides key insights into the mechanisms by which PIM1-mediated phosphorylation of NDRG1 impairs its function, resulting in enhanced cell migration and invasion.

cancer biology↗

bioRxiv2018

Quantitative Assessment of Colorectal Cancer Progression: a Comparative Study of Linear and Nonlinear Microscopy Techniques

BACKGROUND AND AIMSColorectal cancer (CRC) is a disease that can be prevented if is diagnosed and treated at pre-invasive stages. Thus, the monitoring of colonic cancer progression can improve the early diagnosis and detection of malignant lesions in the colon. This monitoring should be performed with appropriate image techniques and be accompanied by proper quantification to minimize subjectivity. We have monitored the mice CRC progression by image deconvolution, two-photon emission fluorescence (TPEF) and second harmonic generation (SHG) microscopies and present different quantization indices for diagnosis.\n\nMETHODSThe Azoxymethane (AOM) / dextran sodium sulfate (DSS) protocol was used. 35 eight-week old male BALB/cCmedc mice were used and distal colon segments were dissected at day zero and fourth, eighth, sixteen, and twenty weeks after injection. These segments were observed with linear and nonlinear optical microscopies and several parameters were used for quantification.\n\nRESULTSCrypt diameter higher than 0.08 mm and increased fluorescence signal intensity in linear images; as well as aspect relation above 0.7 and altered organization reflexed by high-energy values obtained from SHG images, away from those obtained in normal tissues.\n\nCONCLUSIONThe combination of linear and nonlinear signals improve the detection and classification of pathological changes in crypt morphology/distribution and collagen fiber structure/arrangement. In combination with standard screening approaches for CRC, the proposed methods improve the detection of the disease in its early stages, thereby increasing the chances of successful treatment.

cancer biology↗