bioRxiv : the preprint server for biology最新文献

A key question in microbial community analysis is determining which microbial features are associated with community properties such as environmental or health phenotypes. This statistical task is impeded by characteristics of typical microbial community profiling technologies, including sparsity (which can be either technical or biological) and the compositionality imposed by most nucleotide sequencing approaches. Many models have been proposed that focus on how the relative abundance of a feature (e.g. taxon or pathway) relates to one or more covariates. Few of these, however, simultaneously control false discovery rates, achieve reasonable power, incorporate complex modeling terms such as random effects, and also permit assessment of prevalence (presence/absence) associations and absolute abundance associations (when appropriate measurements are available, e.g. qPCR or spike-ins). Here, we introduce MaAsLin 3 (Microbiome Multivariable Associations with Linear Models), a modeling framework that simultaneously identifies both abundance and prevalence relationships in microbiome studies with modern, potentially complex designs. MaAsLin 3 also newly accounts for compositionality with experimental (spike-ins and total microbial load estimation) or computational techniques, and it expands the space of biological hypotheses that can be tested with inference for new covariate types. On a variety of synthetic and real datasets, MaAsLin 3 outperformed current state-of-the-art differential abundance methods in testing and inferring associations from compositional data. When applied to the Inflammatory Bowel Disease Multi-omics Database, MaAsLin 3 corroborated many previously reported microbial associations with the inflammatory bowel diseases, but notably 77% of associations were with feature prevalence rather than abundance. In summary, MaAsLin 3 enables researchers to identify microbiome associations with higher accuracy and more specific association types, especially in complex datasets with multiple covariates and repeated measures.

While much is known about miRNA biogenesis and canonical miRNA targeting, relatively less is understood about miRNA decay. The major miRNA decay pathway in metazoans is mediated through target-directed miRNA degradation (TDMD), in which certain RNAs can 'trigger' miRNA decay. All known triggers for TDMD base pair with the miRNA seed, and extensively base pair on the miRNA 3 prime end, a pattern that supposedly induces a TDMD-competent conformational change of Argonaute (Ago), allowing for miRNA turnover. Here, we utilized Ago1-CLASH to find that the Drosophila transcript Kah contains at least two triggers, a 'trigger cluster', against miR-9b and the miR-279 family. One of these triggers contains minimal/non-canonical 3 prime end base pairing but is still sufficient to induce TDMD of the entire miR-279 family. We found that these clustered triggers likely lack cooperativity, the minimal 3' pairing is required for miR-279 family turnover, and probed the in-cell RNA structure of the Kah trigger cluster. Overall, this study expands the list of endogenous triggers and the unexpectedly complex regulatory network governing miRNA degradation.

SARS coronavirus 2 (SARS-CoV-2) non-structural protein 14 (Nsp14) possesses an N-terminal exonuclease (ExoN) domain that provides a proofreading function for the viral RNA-dependent RNA polymerase and a C-terminal N7-methyltransferase (N7-MTase) domain that methylates viral mRNA caps. Nsp14 also modulates host functions. This includes the activation of NF-κB and downregulation of interferon alpha/beta receptor 1 (IFNAR1). Here we demonstrate that Nsp14 exerts broader effects, activating not only NF-κB responses but also ERK, p38 and JNK MAP kinase (MAPK) signaling, promoting cytokine production. Further, Nsp14 downregulates not only IFNAR1 but also IFN-γ receptor 1 (IFNGR1), impairing cellular responses to both IFNα and IFNγ. IFNAR1 and IFNGR1 downregulation is via a lysosomal pathway and also occurs in SARS-CoV-2 infected cells. Analysis of a panel of Nsp14 mutants reveals a consistent pattern. Mutants that disable ExoN function remain active, whereas N7-MTase mutations impair both pro-inflammatory pathway activation and IFN receptor downregulation. Innate immune modulating functions also require the presence of both the ExoN and N7-MTase domains likely reflecting the need for the ExoN domain for N7-MTase activity. We further identify multi-functional host protein Tollip as an Nsp14 interactor. Interaction requires the phosphoinositide-binding C2 domain of Tollip and sequences C-terminal to the C2 domain. Full length Tollip or regions encompassing the Nsp14 interaction domain are sufficient to counteract both Nsp14-mediated and Nsp14-independent activation of NF-κB. Knockdown of Tollip partially reverses IFNAR1 and IFNGR1 downregulation in SARS-CoV-2 infected cells, suggesting relevance of Nsp14-Tollip interaction for Nsp14 innate immune evasion functions.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records. Using this framework, letrozole and irinotecan were identified as a potential combination therapy, each targeting AD-related gene expression changes in neurons and glial cells, respectively. In an AD mouse model, this combination therapy significantly improved memory function and reduced AD-related pathologies compared to vehicle and single-drug treatments. Single-nuclei transcriptomic analysis confirmed that the therapy reversed disease-associated gene networks in a cell-type-specific manner. These results highlight the promise of cell-type-directed combination therapies in addressing multifactorial diseases like AD and lay the groundwork for precision medicine tailored to patient-specific transcriptomic and clinical profiles.

The genome-wide chromosome conformation capture method, Hi-C, has greatly advanced our understanding of genome organization. However, its quantitative properties, including sensitivity, bias, and linearity, remain challenging to assess. Measuring these properties in vivo is difficult due to the heterogenous and dynamic nature of chromosomal interactions. Here, using Chemically Induced Chromosomal Interaction (CICI) method, we create stable intra- and inter-chromosomal interactions in G1-phase budding yeast across a broad range of contact frequencies. Hi-C analysis of these engineered cell populations demonstrates that static intra-chromosomal loops do not generate Topologically Associated Domains (TADs) and only promote 3D proximity within ~50kb flanking regions. At moderate sequencing depth, Hi-C is sensitive enough to detect interactions occurring in 5-10% of cells. It also shows no inherent bias toward intra- versus inter-chromosomal interactions. Furthermore, we observe a linear relationship between Hi-C signal intensity and contact frequency. These findings illuminate the intrinsic properties of the Hi-C assay and provide a robust framework for its calibration.

The ability to sense, import but also detoxify copper (Cu) has been shown to be crucial for microbial pathogens to survive within the host. Previous studies conducted with the opportunistic human fungal pathogen Cryptococcus neoformans ( Cn ) have revealed two extreme Cu environments encountered during infection: A high Cu environment within the lung and a low Cu environment within the brain. However, how Cn senses these different host Cu microenvironments, and the consequences of a blunted Cu stress adaption for pathogenesis, are not well understood. In contrast to other fungi, Cn has a single transcription factor, Cuf1, to regulate adaptive responses to both high- and low-Cu stress. Sequence analysis of Cn Cuf1 identified three conserved cysteine (Cys)-rich regions that may play a role in Cu sensing. We mutated the 1 ^st Cys-rich region within the CUF1 gene to investigate its role for Cn high Cu stress sensing. Subsequent analysis of Cuf1 transcriptional activity and target gene promoter binding demonstrated that the 1 ^st Cys-rich region is required for Cuf1 transcriptional activity in high Cu stress. We performed an inhalational murine infection to analyze the effects of a blunted high Cu stress response on pathogenesis. No significant differences in lung fungal burden were observed based on variable Cuf1 activity. However, strains with defective high Cu stress regulation induced a markedly altered immune response in mice. Based on these findings, we hypothesize that Cuf1-driven high Cu responses are not required for initial survival but instead modulate immune recognition and inflammation within the mouse lung.

Importance: Copper is an essential micronutrient required for survival in all kingdoms of life as it is used as a catalytic cofactor for many essential processes in the cell. In turn, this reactivity of copper ions makes elevated levels of free copper toxic for the cell. This dual nature of copper-essential for life but toxic at elevated levels- is used by our innate immune system in a process called nutritional immunity to combat and kill invading pathogens. In this work we explore how the fungal human pathogen Cryptococcus neoformans senses high copper stress, a copper microenvironment encountered within the host lung. We identified a specific cysteine-rich region within the copper responsive transcription factor Cuf1 to be essential for high copper stress sensing. Mutation of this region led to an impaired high copper stress adaptation, which did not affect fitness of the yeast but did impact immune recognition and inflammation inside the host lung.

Biogenesis of circular RNA usually involves a backsplicing reaction where the downstream donor site is ligated to the upstream acceptor site by the spliceosome. For this reaction to occur, it is hypothesized that these sites must be in proximity. Inverted repeat sequences, such as Alu elements, in the upstream and downstream introns are predicted to base-pair and represent one mechanism for inducing proximity. Here, we investigate the pre-mRNA structure of the human HIPK3 gene at exon 2, which forms a circular RNA via backsplicing. We leverage multiple chemical probing techniques, including the recently developed SHAPE- JuMP strategy, to characterize secondary and tertiary interactions in the pre- mRNA that govern backsplicing. Our data confirm that the antisense Alu elements, AluSz(-) and AluSq2(+) in the upstream and downstream introns, form a highly- paired interaction. Circularization requires formation of long-range Alu-mediated base pairs but does not require the full-length AluSq2(+). In addition to confirming long-range base pairs, our SHAPE-JuMP data identified multiple long-range interactions between non-pairing nucleotides. Genome-wide analysis of inverted repeats flanking circular RNAs confirm that their presence favors circularization, but the overall effect is modest. Together these results suggest that secondary structure considerations alone cannot fully explain backsplicing and additional interactions are key.

The deposition of amyloid-β (Aβ) protein in the human brain is a hallmark of Alzheimer's disease and is related to cognitive decline. However, the relationship between early Aβ deposition and future cognitive impairment remains poorly understood, particularly concerning its spatial distribution and network-level effects. Here, we employed a cross-validated machine learning approach and investigated whether integrating subject-specific brain connectome information with Aβ burden measures improves predictive validity for subsequent cognitive decline. Baseline regional Aβ pathology measures from positron emission tomography (PET) imaging predicted prospective cognitive decline. Incorporating structural connectome, but not functional connectome, information into the Aβ measures improved predictive performance. We further identified a neuropathological signature pattern linked to future cognitive decline, which was validated in an independent cohort. These findings advance our understanding of how Aβ pathology relates to brain networks and highlight the potential of network-based metrics for Aβ-PET imaging to identify individuals at higher risk of cognitive decline.

Single-cell RNA sequencing (scRNA-seq) maps gene expression heterogeneity within a tissue. However, identifying biological signals in this data is challenging due to confounding technical factors, sparsity, and high dimensionality. Data factorization methods address this by separating and identifying signals in the data, such as gene expression programs, but the resulting factors must be manually interpreted. We developed Single-Cell Interpretable REsidual Decomposition (sciRED) to improve the interpretation of scRNA-seq factor analysis. sciRED removes known confounding effects, uses rotations to improve factor interpretability, maps factors to known covariates, identifies unexplained factors that may capture hidden biological phenomena and determines the genes and biological processes represented by the resulting factors. We apply sciRED to multiple scRNA-seq datasets and identify sex-specific variation in a kidney map, discern strong and weak immune stimulation signals in a PBMC dataset, reduce ambient RNA contamination in a rat liver atlas to help identify strain variation, and reveal rare cell type signatures and anatomical zonation gene programs in a healthy human liver map. These demonstrate that sciRED is useful in characterizing diverse biological signals within scRNA-seq data.

Pathogenic coding mutations are prevalent in human neuronal transcription factors (TFs) but how they disrupt development is poorly understood. Lmx1b is a master transcriptional regulator of postmitotic Pet1 neurons that give rise to mature serotonin (5-HT) neurons; over two hundred pathogenic heterozygous mutations have been discovered in human LMX1B, yet their impact on brain development has not been investigated. Here, we developed mouse models with different LMX1B DNA-binding missense mutations. Missense heterozygosity broadly altered Pet1 neuron transcriptomes, but expression changes converged on axon and synapse genes. Missense heterozygosity effected highly specific deficits in the postnatal maturation of forebrain serotonin axon arbors, primarily in the hippocampus and motor cortex, which was associated with spatial memory defects. Digital genomic footprinting (DGF) revealed that missense heterozygosity caused complete loss of Lmx1b motif protection and chromatin accessibility at sites enriched for a distal active enhancer/active promoter histone signature and homeodomain binding motifs; at other bound Lmx1b motifs, varying levels of losses, gains or no change in motif binding and accessibility were found. The spectrum of footprint changes was strongly associated with synapse and axon genes. Further, Lmx1b missense heterozygosity caused wide disruption of Lmx1b-dependent GRNs comprising diverse TFs expressed in Pet1 neurons. These findings reveal an unanticipated continuum of Lmx1b missense-forced perturbations on Pet1 neuron regulatory element TF binding and accessibility. Our work illustrates the power of DGF for gaining unique insight into how TF missense mutations interfere with developing neuronal GRNs.

Significance statement: We modeled human LMX1B missense mutations in mice to explore how they disrupt brain serotonin neuron development. Missense heterozygosity selectively impaired postnatal formation of serotonin axon arbors throughout the forebrain, notably in the hippocampus and motor cortex. DGF revealed that Lmx1b missense heterozygosity exerted a continuum of footprint changes associated with synapse and axon gene expression. Footprint changes ranged from total eliminations to partial losses and gains within the Pet1 neuronal epigenome. LMX1B missense mutations may cause human brain pathogenesis by selectively disrupting cis regulatory elements controlling 5-HT axon arbor formation thus impairing 5-HT delivery to presynaptic release sites.