Biology subjects

Klein, N.

Publications and source records attributed to Klein, N..

6 recordsLinked to original sources

bioRxiv2025

Sex Disparities in Gastric Cancer Tumor Mutation Burden and Gene Mutation Patterns

Significant sex-related differences exist in gastric cancer, yet the molecular basis remains unclear. Tumor mutational burden (TMB) correlates with successful immune checkpoint inhibitor therapy, but TMB varies across different cancers, and evidence regarding sex-specific differences remains inconsistent. We analyzed sex-specific single-nucleotide mutations in gastric cancer using The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) dataset and found that females had significantly higher autosomal TMB. We identified 1,052 sexually dimorphic genes, with enrichment analyses highlighting distinct biological pathways in each sex. These genes overlap key cancer pathways, emphasizing their role in tumorigenesis. Differing co-mutation patterns--with females exhibiting more stable patterns--enabled a machine-learning model to predict tumor sex from mutation profiles. Our findings suggest that male and female gastric cancers could represent distinct diseases, underscoring the need for sex-specific diagnostic markers and personalized therapies.

cancer biology↗

bioRxiv2024

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. Serpine1 mRNA-binding protein 1 (SERBP1) is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. We defined SERBP1s interactome, uncovered novel roles in splicing, cell division and ribosomal biogenesis, and showed its participation in pathological stress granules and Tau aggregates in Alzheimers brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.

genomics↗

bioRxiv2023

Divergent associations of slow-wave sleep vs. REM sleep with plasma amyloid-beta

BackgroundRecent evidence shows that during slow-wave sleep (SWS), the brain is cleared from potentially toxic metabolites, such as the amyloid-beta protein. Poor sleep or elevated cortisol levels can worsen amyloid-beta clearance, potentially leading to the formation of amyloid plaques, a neuropathological hallmark of Alzheimers disease. Here, we explore how nocturnal neural and endocrine activity affects amyloid-beta fluctuations in the peripheral blood as a reflection of cerebral clearance. MethodsSimultaneous polysomnography and all-night blood sampling were acquired in 60 healthy volunteers aged 20-68 years old. Nocturnal plasma concentrations of two amyloid-beta species (amyloid-beta-40 and amyloid-beta-42), cortisol, and growth hormone were assessed every 20 minutes from 23:00-7:00. Amyloid-beta fluctuations were modeled with sleep stages, (non)-oscillatory power, and hormones as predictors while controlling for age and multiple comparisons. Time lags between the predictors and amyloid-beta ranged from 20 to 120min. FindingsThe amyloid-beta-40 and amyloid-beta-42 levels correlated positively with growth hormone concentrations, SWS proportion, slow-wave (0.3-4Hz) oscillatory and high-band (30-48Hz) non-oscillatory power, but negatively with cortisol concentrations and rapid eye movement sleep (REM) proportion measured 40-100min before (all t-values>|3|, p-values<0.003). Older participants showed higher amyloid-beta-40 levels. InterpretationSlow-wave oscillations are associated with higher plasma amyloid-beta levels, reflecting their contribution to cerebral amyloid-beta clearance across the blood-brain barrier. REM sleep is related to decreased amyloid-beta plasma levels; however, this link may reflect passive aftereffects of SWS and not REMs effects per se. Strong associations between cortisol, growth hormone, and amyloid-beta presumably reflect the sleep-regulating role of the corresponding releasing hormones. A positive association between age and amyloid-beta-40 may indicate that peripheral clearance becomes less efficient with age. Our study provides important insights into the specificity of different sleep features effects on brain clearance and suggests that cortisol nocturnal fluctuations may serve as a new marker of clearance efficiency.

neuroscience↗

bioRxiv2020

Tension causes structural unfolding of intracellular intermediate filaments

Intermediate filament (IF) proteins are a class of proteins that constitute different filamentous structures in mammalian cells. As such, IF proteins are part of the load-bearing cytoskeleton and support the nuclear envelope. Molecular dynamics simulations have shown that IF proteins undergo secondary structural changes to compensate mechanical loads, which has been confirmed by experimental in vitro studies on IF hydrogels. However, the structural response of intracellular IF to mechanical load has yet to be elucidated in cellulo. Here, we use in situ nonlinear Raman imaging combined with multivariate data analysis to quantify the intracellular secondary structure of the IF cytoskeletal protein vimentin under different states of cellular tension. We find that cells under native cellular tension contain more unfolded vimentin than chemically or physically relaxed specimens. This indicates that unfolding of IF proteins occurs intracellularly when sufficient forces are applied, suggesting that IF structures act as local force sensors in the cell to mark locations under large mechanical tension.

biophysics↗

bioRxiv2019

Cross-transmission is not the source of new Mycobacteirum abscessus infections in a multi-centre cohort of cystic fibrosis patients

BackgroundMycobacterium abscessus is an extensively drug resistant pathogen that causes pulmonary disease particularly in cystic fibrosis (CF) patients. Identifying direct patient-to-patient transmission of M. abscessus is critically important in directing infection control policy for the management of risk in CF patients. A variety of clinical labs have used molecular epidemiology to investigate transmission. However there is still conflicting evidence as to how M. abscessus is acquired and whether cross-transmission occurs. Recently labs have applied whole-genome sequencing (WGS) to investigate this further and in this study we investigate whether WGS can reliably identify cross-transmission in M. abscessus.\n\nMethodsWe retrospectively sequenced the whole genomes of 145 M. abscessus isolates from 62 patients seen at four hospitals in two countries over 16 years.\n\nResultsWe have shown that a comparison of a fixed number of core single nucleotide variants (SNVs) alone cannot be used to infer cross-transmission in M. abscessus but does provide enough information to replace multiple existing molecular assays. We detected one episode of possible direct patient-to-patient transmission in a sibling pair. We found that patients acquired unique M. abscessus strains even after spending considerable time on the same wards with other M. abscessus positive patients.\n\nConclusionsThis novel analysis has demonstrated that the majority of patients in this study have not acquired M. abscessus through direct patient-patient transmission or a common reservoir. Tracking transmission using WGS will only realise its full potential with proper environmental screening as well as patient sampling.\n\nKey pointsO_LIWhole genome sequencing should replace current molecular typing used routinely in clinical microbiology laboratories.\nC_LIO_LIPatient-to-patient spread of M. abscessus is not common.\nC_LIO_LIEnvironmental screening may provide a better understanding acquisition of M. abscessus infections.\nC_LI

microbiology↗

bioRxiv2017

A perturbation model of the gut microbiome’s response to antibiotics

Treatment with antibiotics is one of the most extreme perturbations to the human microbiome. Even standard courses of antibiotics dramatically reduce the microbiomes diversity and can cause transitions to dysbiotic states. Conceptually, this is often described as a stability landscape: the microbiome sits in a landscape with multiple stable equilibria, and sufficiently strong perturbations can shift the microbiome from its normal equilibrium to another state. However, this picture is only qualitative and has not been incorporated in previous mathematical models of the effects of antibiotics. Here, we outline a simple quantitative model based on the stability landscape concept and demonstrate its success on real data. Our analytical impulse-response model has minimal assumptions with three parameters. We fit this model in a Bayesian framework to previously published data on the year-long effects of four common antibiotics (ciprofloxacin, clindamycin, minocycline, and amoxicillin) on the gut and oral microbiomes, allowing us to compare parameters between antibiotics and microbiomes. Furthermore, using Bayesian model selection we find support for a long-term transition to an alternative microbiome state after courses of ciprofloxacin and clindamycin in both the gut and salivary microbiomes. Quantitative stability landscape frameworks are an exciting avenue for future microbiome modelling.

microbiology↗