Predictive Biology (United States)

SummaryLow-affinity transcription factor (TF) motifs are an important element of the cis-regulatory code, yet they are notoriously difficult to map and mechanistically incompletely understood, limiting our ability to interpret non-coding variation in development, evolution, and disease. Here we investigate their role in pioneering and leverage sequence-to-profile models of chromatin accessibility in mouse embryonic stem cells to reliably map and interpret low-affinity motifs across the genome. We find that low-affinity motifs have outsized effects by cooperating with nearby motifs through intra-nucleosomal soft syntax. By modeling nucleosome-mediated cooperativity with a kinetic model, we discover and validate that pioneer cooperativity makes a motif operate at higher pioneering ranges across changing TF concentrations, thereby raising the regulatory potential. These results show that low-affinity motifs can be accurately mapped, shape the properties of developmental enhancers and likely play a widespread role in fine-tuning enhancers during evolution.

1.AbstractRecent advances in cognitive neuroscience emphasise the importance of healthy white matter (WM) in optimal behavioural functioning. It is now widely accepted that brain connectivity via WM contributes to the emergence of behaviour. However, the association between the microstructure of WM fibres and behaviour is poorly understood. This is in part due to indirect and overlapping methods of assessing microstructure, and the use of overly simplistic approaches in assessing behaviour. Here, we used the Mahalanobis Distance (D2) to integrate 10 metrics of WM derived from multimodal neuroimaging that have strong ties to microstructure. The D2 metric was chosen because it accounts for metrics’ covariance as it measures the voxelwise distance between every subject and the average; thus providing a robust multiparametric assessment of microstructure. To examine WM-behaviour associations, we used multivariate correlation to examine the voxelwise correlates of 2 cognitive and 2 motor tasks, which allowed us to compare within and across domains in WM. We observed that behaviour is organised in cognitive, motor, and integrative variables that are widespread in their associations with WM, from frontal to parietal regions. Our results highlight the complex nature of microstructure and behaviour, and show the need for multivariate modelling when examining brain-behaviour associations.

Long-read metagenomic sequencing is a powerful approach for cataloging the microbial diversity present in complex microbiomes, including the human gut microbiome. We performed a deep-sequencing experiment using PacBio HiFi reads to obtain metagenome-assembled genomes (MAGs) from a pooled human gut microbiome. We performed long-read metagenome assembly using two methods (hifiasm-meta, metMDBG), used improved bioinformatic and proximity ligation binning strategies to cluster contigs and identify MAGs, and developed a novel framework to compare and consolidate MAGs (pb-MAG-mirror). We found proximity ligation binning yielded more MAGs than bioinformatic binning, but our novel comparison framework resulted in higher MAG yields than either binning strategy individually. In total, from 255 Gbp of total HiFi data we produced 595 total MAGs (including 175 high-quality MAGs) using hifiasm-meta, and 547 total MAGs (including 277 high-quality MAGs) with metaMDBG. Hifiasm-meta assembled almost twice as many strain-level MAGs as metaMDBG (246 vs. 156), but both assembly methods produced up to five strains for a species. Approximately 85% of the MAGs were assigned to known species, but we recovered >35 high-quality MAGs that represent uncultured diversity. Based on strict similarity scores, we found 125 MAGs were unequivocally shared across the assembly methods at the strain level, representing ~22% of the total MAGs recovered per method. Finally, we detected more total viral sequences in the metaMDBG assembly versus the hifiasm-meta assembly (~6,700 vs. ~4,500). Overall, we find the use of HiFi sequencing, improved metagenome assembly methods, and complementary binning strategies is highly effective for rapidly cataloging microbial genomes in complex microbiomes.

During alveolar repair, alveolar type 2 (AT2) epithelial cell progenitors rapidly proliferate and differentiate into flat AT1 epithelial cells. Failure of normal alveolar repair mechanisms can lead to loss of alveolar structure (emphysema) or development of fibrosis, depending on the type and severity of injury. To test if β1-containing integrins are required during repair following acute injury, we administered E. coli lipopolysaccharide (LPS) by intratracheal injection to mice with a postdevelopmental deletion of β1 integrin in AT2 cells. While control mice recovered from LPS injury without structural abnormalities, β1-deficient mice had more severe inflammation and developed emphysema. In addition, recovering alveoli were repopulated with an abundance of rounded epithelial cells coexpressing AT2 epithelial, AT1 epithelial, and mixed intermediate cell state markers, with few mature type 1 cells. AT2 cells deficient in β1 showed persistently increased proliferation after injury, which was blocked by inhibiting NF-κB activation in these cells. Lineage tracing experiments revealed that β1-deficient AT2 cells failed to differentiate into mature AT1 epithelial cells. Together, these findings demonstrate that functional alveolar repair after injury with terminal alveolar epithelial differentiation requires β1-containing integrins.

Abstract Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. Here we dramatically relax GWAS stringency by orders of magnitude and apply GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks from diverse lines of evidence. From multiple GWAS summary statistics of suicide attempt, a complex psychiatric phenotype, GRIN identified additional genes that replicated across independent cohorts and retained genes that were more biologically interrelated despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways to influence suicidal behavior and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate that GRIN is a useful community resource for improving the signal to noise ratio of GWAS results.

Abstract Hard graph problems are ubiquitous in Bioinformatics, inspiring the design of specialized Fixed-Parameter Tractable algorithms, many of which rely on a combination of tree-decomposition and dynamic programming. The time/space complexities of such approaches hinge critically on low values for the treewidth tw of the input graph. In order to extend their scope of applicability, we introduce the Tree-Diet problem, i.e. the removal of a minimal set of edges such that a given tree-decomposition can be slimmed down to a prescribed treewidth tw. Our rationale is that the time gained thanks to a smaller treewidth in a parameterized algorithm compensates the extra post-processing needed to take deleted edges into account. Our core result is an FPT dynamic programming algorithm for Tree-Diet, using 2^O(tw)n time and space. We complement this result with parameterized complexity lower-bounds for stronger variants (e.g., NP-hardness when tw or tw − tw is constant). We propose a prototype implementation for our approach which we apply on difficult instances of selected RNA-based problems: RNA design, sequence-structure alignment, and search of pseudoknotted RNAs in genomes, revealing very encouraging results. This work paves the way for a wider adoption of tree-decomposition-based algorithms in Bioinformatics.

Backgroud: Chimeric Antigen Receptor (CAR) T-cell therapy targeting CD19 has shown efficacy against B-cell lymphomas, but a significant proportion of patients will eventually relapse. The histopathological and molecular changes associated with treatment failure are still largely unknown. Methods: To clarify this point, we have analyzed 16 sequential tumor samples from 6 patients (pts) prior CAR-T therapy (Pre-CAR) and at relapse (Post-CAR), using immunohistochemistry (IHC), FISH, array-CGH (CGH), Large Panel Next Generation Sequencing (NGS), RNA sequencing (RNA seq) and genome–scale DNA methylation (METH). Results: The initial diagnosis was diffuse large B-cell lymphoma (DLBCL, n = 5) and Burkitt's lymphoma (BL, n = 1). In 3/6 pts (DLBCLs), the morphological, phenotypical and FISH patterns remained mostly similar in paired sequential samples, except for a slight decrease in CD19 staining whereas CD20, CD79A and PAX5 remained unchanged. These 3 cases exhibited isolated rearrangements of BCL2, BCL6 and MYC, respectively. CGH showed an increase in the number of chromosomal alterations in Post-CAR. NGS showed the occurrence of additional pathogenic variants in Post-CAR, including the PI3K pathway (PIK3R1, PIK3R2, PIK3C2G) and genes associated with aggressive tumor behavior (INPP4B, SYNE1, TBL1XR1). In contrast, the 3 remaining cases (2 DLBCLs and 1 BL) showed loss or drastic decrease of most B-cell markers including CD19, CD20, CD79A and PAX5. In 2 cases, the relapse samples displayed a complete morpho-phenotypic shift, with emergence of T-cell markers (CD2, CD3 and CD7) in 1 case; or expression of histiocytic markers (CD163, CD68) together with a histiocyte-like morphology in the other case. Clonality analysis showed identical clonal IGH rearrangements in sequential samples from both cases. NGS showed the occurrence of KRAS, MAP2K1 and SF3B1 mutations in Post-CAR. A PAX5 mutation was detected in the Post-CAR sample with aberrant T-cell phenotype, which also showed reduced mRNA expression of most B-cell genes and increased methylation of the corresponding promoters. Conclusions: These preliminary results indicate that CAR-T resistance in B-NHLs can be associated with profound dysregulation of B-cell differentiation and upregulation of genes involved in tumor proliferation. The occurrence of mutations in the PI3K and KRAS pathways suggests that appropriate targeted therapies could be useful in CAR-T resistant pts. Post-CAR aberrant T-cell phenotype brings a proof of concept of in vivo trans-differentiation from B-cell into T-cell lymphoma program due to therapeutical selection pressure. Pathologists have to be aware of such unexpected features as potential diagnostic pitfalls. Keywords: Pathology and Classification of Lymphomas No conflicts of interests pertinent to the abstract.

Both healthy aging and Alzheimer’s disease (AD) are characterized by concurrent alterations in several biological factors. However, generative brain models of aging and AD are limited in incorporating the measures of these biological factors at different spatial resolutions. Here, we propose a personalized bottom-up spatiotemporal brain model that accounts for the direct interplay between hundreds of RNA transcripts and multiple macroscopic neuroimaging modalities (PET, MRI). In normal elderly and AD participants, the model identifies top genes modulating tau and amyloid-β burdens, vascular flow, glucose metabolism, functional activity, and atrophy to drive cognitive decline. The results also revealed that AD and healthy aging share specific biological mechanisms, even though AD is a separate entity with considerably more altered pathways. Overall, this personalized model offers novel insights into the multiscale alterations in the elderly brain, with important implications for identifying effective genetic targets for extending healthy aging and treating AD progression.