Biology subjects

Langer, B.

Publications and source records attributed to Langer, B..

5 recordsLinked to original sources

bioRxiv2025

Prefrontal and Subcortical Value Representation during Explore-Exploit Decision-Making and Suicide Attempts

BackgroundThis study aims to understand learning and decision-making in suicidal behavior by investigating temporal dynamics of reward value encoding in individuals with late-life depression and a history of suicide attempts. MethodsIn a retrospective case-control study, 134 older adults (33 with depression and history of suicide attempts, 29 with depression and suicidal ideation but no past attempts, 32 with depression and no suicidal ideation/past attempts, and 40 psychiatrically healthy controls) completed an explore-exploit decision-making task during functional MRI (fMRI). Multilevel models of deconvolved fMRI time series, time-locked to trial events, interrogated whether temporal patterns of reward value encoding was associated with suicidal behavior. ResultsSuicidal behavior in general was associated with blunted ventral PFC (vPFC) value signals, but profiles varied as a function of attempt lethality. Specifically, low-lethality suicide attempts and excessive behavioral shifts were associated with abolished phasic responses to value updates in the default network vPFC and its connected regions, including the striatum, amygdala, and hippocampus. Additionally, an unexpected pattern of sustained negative value responses was observed in vPFC and striatal control subregions, and hippocampus of high-lethality suicide attempters. ConclusionsDiverging patterns of decision-related responses may reflect different paths toward suicidal behavior. Impaired value updating in individuals with low-lethality suicide attempts suggests a failure to integrate recent outcomes alongside prior experience, potentially relating to over-reactivity to stressors and a lower threshold for suicide attempts. In contrast, increased control network responses to difficult choices in high-lethality attempters may underlie cognitive constriction and consideration of a narrow set of potential solutions.

neuroscience↗

bioRxiv2024

VILOCA: Sequencing quality-aware haplotype reconstruction and mutation calling for short- and long-read data

RNA viruses exist in large heterogeneous populations within their host. The structure and diversity of virus populations affects disease progression and treatment outcomes. Next-generation sequencing allows detailed viral population analysis, but inferring diversity from error-prone reads is challenging. Here, we present VILOCA, a method for mutation calling and reconstruction of local haplotypes from short- and long-read viral sequencing data. Local haplotypes refer to genomic regions that have approximately the length of the input reads. VILOCA recovers local haplotypes by using a Dirichlet process mixture model to cluster reads around their unobserved haplotypes and leveraging quality scores of the sequencing reads. We assessed the performance of VILOCA in terms of mutation calling and haplotype reconstruction accuracy on simulated and experimental Illumina, PacBio, and Oxford Nanopore data. On simulated and experimental Illumina data, VILOCA performed better or similar to existing methods. On the simulated long-read data, VILOCA is able to recover on average 82% of the ground truth mutations with perfect precision compared to only 64% recall and 90% precision of the second-best method. In summary, VILOCA provides significantly improved accuracy in mutation and haplotype calling, especially for long-read sequencing data, and therefore facilitates the comprehensive characterization of heterogeneous within-host viral populations.

bioinformatics↗

bioRxiv2023

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

bioinformatics↗

bioRxiv2021

Murine ex vivo cultured alveolar macrophages provide a novel tool to study tissue-resident macrophage behavior and function

Tissue-resident macrophages are of vital importance as they preserve tissue homeostasis in all mammalian organs. Nevertheless, appropriate cell culture models are still limited. Here, we propose a novel culture model to study and expand murine primary alveolar macrophages (AMs), the tissue-resident macrophages of the lung, in vitro over several months. By providing a combination of GM-CSF, TGF{beta} and the PPAR{gamma} activator rosiglitazone, we maintain and expand mouse ex vivo cultured AMs, short mexAMs, over several months. MexAMs maintain typical morphologic features and stably express primary AM surface markers throughout in vitro culture. They respond to microbial ligands and exhibit an AM-like transcriptional profile, including the expression of AM specific transcription factors. Furthermore, when transferred into AM deficient mice, mexAMs efficiently engraft in the lung and fulfill key macrophage functions leading to a significantly reduced surfactant load in those mice. Altogether, mexAMs provide a novel, simple and versatile tool to study AM behavior in homeostasis and disease settings. KEYPOINTSO_LIA novel method to culture and expand primary alveolar macrophages over several months ex vivo C_LIO_LIMurine ex vivo cultured alveolar macrophages (mexAMs) restore lung function in a murine pulmonary alveolar proteinosis model C_LI

immunology↗

bioRxiv2017

Phenotype loss is associated with widespread divergence of the gene regulatory landscape in evolution

Detecting the genomic changes underlying phenotypic changes between species is a main goal of evolutionary biology and genomics. Evolutionary theory predicts that changes in cis-regulatory elements are important for morphological changes. Here, we combine genome sequencing and functional genomics with genome-wide comparative analyses to investigate the fate of regulatory elements in lineages that lost morphological traits. We first show that limb loss in snakes is associated with widespread divergence of limb regulatory elements. We next show that eye degeneration in subterranean mammals is associated with widespread divergence of eye regulatory elements. In both cases, sequence divergence results in an extensive loss of relevant transcription factor binding sites. Importantly, diverged regulatory elements are associated with key genes required for normal limb patterning or normal eye development and function, suggesting that regulatory divergence contributed to the loss of these phenotypes. Together, our results provide the first evidence that genome-wide decay of the phenotype-specific cis-regulatory landscape is a hallmark of lost morphological traits.

genomics↗