SMARCAD1 ATPase activity is required to silence endogenous retroviruses in embryonic stem cells

OpenTn5: Open-Source Resource for Robust and Scalable Tn5 Transposase Purification and Characterization

Tagmentation combines DNA fragmentation and sequencing adapter addition by leveraging the transposition activity of the bacterial cut-and-paste Tn5 transposase, to enable efficient sequencing library preparation. Here we present an open-source protocol for the generation of multi-purpose hyperactive Tn5 transposase, including its benchmarking in CUT&Tag, bulk and single-cell ATAC-seq. The OpenTn5 protocol yields multi-milligram quantities of pG-Tn5 E54K, L372P protein per liter of E. coli culture, sufficient for thousands of tagmentation reactions and the enzyme retains activity in storage for more than a year.

Frequent transitions in self-assembly across the evolution of a central metabolic enzyme

Many enzymes assemble into homomeric protein complexes comprising multiple copies of one protein. Because structural form is usually assumed to follow function in biochemistry, these assemblies are thought to evolve because they provide some functional advantage. In many cases, however, no specific advantage is known and, in some cases, quaternary structure varies among orthologs. This has led to the proposition that self-assembly may instead vary neutrally within protein families. The extent of such variation has been difficult to ascertain because quaternary structure has until recently been difficult to measure on large scales. Here, we employ mass photometry, phylogenetics, and structural biology to interrogate the evolution of homo-oligomeric assembly across the entire phylogeny of prokaryotic citrate synthases - an enzyme with a highly conserved function. We discover a menagerie of different assembly types that come and go over the course of evolution, including cases of parallel evolution and reversions from complex to simple assemblies. Functional experiments in vitro and in vivo indicate that evolutionary transitions between different assemblies do not strongly influence enzyme catalysis. Our work suggests that enzymes can wander relatively freely through a large space of possible assemblies and demonstrates the power of characterizing structure-function relationships across entire phylogenies.

MICOS Complex Loss Governs Age-Associated Murine Mitochondrial Architecture and Metabolism in the Liver, While Sam50 Dictates Diet Changes

The liver, the largest internal organ and a metabolic hub, undergoes significant declines due to aging, affecting mitochondrial function and increasing the risk of systemic liver diseases. How the mitochondrial three-dimensional (3D) structure changes in the liver across aging, and the biological mechanisms regulating such changes confers remain unclear. In this study, we employed Serial Block Face-Scanning Electron Microscopy (SBF-SEM) to achieve high-resolution 3D reconstructions of murine liver mitochondria to observe diverse phenotypes and structural alterations that occur with age, marked by a reduction in size and complexity. We also show concomitant metabolomic and lipidomic changes in aged samples. Aged human samples reflected altered disease risk. To find potential regulators of this change, we examined the Mitochondrial Contact Site and Cristae Organizing System (MICOS) complex, which plays a crucial role in maintaining mitochondrial architecture. We observe that the MICOS complex is lost during aging, but not Sam50. Sam50 is a component of the sorting and assembly machinery (SAM) complex that acts in tandem with the MICOS complex to modulate cristae morphology. In murine models subjected to a high-fat diet, there is a marked depletion of the mitochondrial protein SAM50. This reduction in Sam50 expression may heighten the susceptibility to liver disease, as our human biobank studies corroborate that Sam50 plays a genetically regulated role in the predisposition to multiple liver diseases. We further show that changes in mitochondrial calcium dysregulation and oxidative stress accompany the disruption of the MICOS complex. Together, we establish that a decrease in mitochondrial complexity and dysregulated metabolism occur with murine liver aging. While these changes are partially be regulated by age-related loss of the MICOS complex, the confluence of a murine high-fat diet can also cause loss of Sam50, which contributes to liver diseases. In summary, our study reveals potential regulators that affect age-related changes in mitochondrial structure and metabolism, which can be targeted in future therapeutic techniques.

PROTAC-induced Protein Functional Dynamics in Targeted Protein Degradation

PROteolysis TArgeting Chimeras (PROTACs) are small molecules that induce target protein degradation via the ubiquitin proteasome system. PROTACs recruit the target protein and E3 ligase; a critical first step is forming a ternary complex. However, while the formation a ternary complex is crucial, it may not always guarantee successful protein degradation. The dynamics of the PROTAC induced degradation complex play a key role in ubiquitination and subsequent degradation. In this study, we computationally modelled protein complex structures and dynamics associated with a series of PROTACs featuring different linkers to investigate why these PROTACs, all of which formed ternary complexes with Cereblon (CRBN) E3 ligase and the target protein bromodomain containing protein 4 (BRD4BD1), exhibited varying degrees of degradation potency. We constructed the degradation machinery complexes with Culling Ring Ligase 4A (CRL4A) E3 ligase scaffolds. Through atomistic molecular dynamics simulations, we illustrated how PROTAC dependent protein dynamics facilitate the arrangement of surface lysine residues of BRD4BD1 into the catalytic pocket of E2/ubiquitin for ubiquitination. Despite featuring identical warheads in this PROTAC series, the linkers were found to affect the residue interaction networks, and thus governing the essential motions of the entire degradation machine for ubiquitination. These findings offer a dynamic perspective on ligand induced protein degradation, providing insights to guide future PROTAC design endeavors.

Neuronal Coupling Modes Show Differential Development in the Early Cortical Activity Networks of Human Newborns

The third trimester is a critical period for the development of functional networks that support the lifelong neurocognitive performance, yet the emergence of neuronal coupling in these networks is poorly understood. Here, we used longitudinal high-density electroencephalographic recordings from preterm infants during the period from 33 to 45 weeks of conceptional age (CA) to characterize early spatiotemporal patterns in the development of local cortical function and the intrinsic coupling modes [ICMs; phase-phase (PPCs), amplitude-amplitude (AACs), and phase-amplitude correlations (PACs)]. Absolute local power showed a robust increase with CA across the full frequency spectrum, while local PACs showed sleep state-specific, biphasic development that peaked a few weeks before normal birth. AACs and distant PACs decreased globally at nearly all frequencies. In contrast, the PPCs showed frequency- and region-selective development, with an increase of coupling strength with CA between frontal, central, and occipital regions at low-delta and alpha frequencies together with a wider-spread decrease at other frequencies. Our findings together present the spectrally and spatially differential development of the distinct ICMs during the neonatal period and provide their developmental templates for future basic and clinical research.

Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change

Extracellular signals induce changes to molecular programs that modulate multiple cellular phenotypes, including proliferation, motility, and differentiation status. The connection between dynamically adapting phenotypic states and the molecular programs that define them is not well understood. Here we develop data-driven models of single-cell phenotypic responses to extracellular stimuli by linking gene transcription levels to "morphodynamics" - changes in cell morphology and motility observable in time-lapse image data. We adopt a dynamics-first view of cell state by grouping single-cell trajectories into states with shared morphodynamic responses. The single-cell trajectories enable development of a first-of-its-kind computational approach to map live-cell dynamics to snapshot gene transcript levels, which we term MMIST, Molecular and Morphodynamics-Integrated Single-cell Trajectories. The key conceptual advance of MMIST is that cell behavior can be quantified based on dynamically defined states and that extracellular signals alter the overall distribution of cell states by altering rates of switching between states. We find a cell state landscape that is bound by epithelial and mesenchymal endpoints, with distinct sequences of epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET) intermediates. The analysis yields predictions for gene expression changes consistent with curated EMT gene sets and provides a prediction of thousands of RNA transcripts through extracellular signal-induced EMT and MET with near-continuous time resolution. The MMIST framework leverages true single-cell dynamical behavior to generate molecular-level omics inferences and is broadly applicable to other biological domains, time-lapse imaging approaches and molecular snapshot data.

Fine-mapping causal tissues and genes at disease-associated loci

Heritable diseases often manifest in a highly tissue-specific manner, with different disease loci mediated by genes in distinct tissues or cell types. We propose Tissue-Gene Fine-Mapping (TGFM), a fine-mapping method that infers the posterior probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing GWAS summary statistics (and in-sample LD) and leveraging eQTL data from diverse tissues to build cis-predicted expression models; TGFM also assigns PIPs to causal variants that are not mediated by gene expression in assayed genes and tissues. TGFM accounts for both co-regulation across genes and tissues and LD between SNPs (generalizing existing fine-mapping methods), and incorporates genome-wide estimates of each tissue's contribution to disease as tissue-level priors. TGFM was well-calibrated and moderately well-powered in simulations; unlike previous methods, TGFM was able to attain correct calibration by modeling uncertainty in cis-predicted expression models. We applied TGFM to 45 UK Biobank diseases/traits (average N = 316K) using eQTL data from 38 GTEx tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease/trait, of which 11% were gene-tissue pairs. Implicated gene-tissue pairs were concentrated in known disease-critical tissues, and causal genes were strongly enriched in disease-relevant gene sets. Causal gene-tissue pairs identified by TGFM recapitulated known biology (e.g., TPO-thyroid for Hypothyroidism), but also included biologically plausible novel findings (e.g., SLC20A2-artery aorta for Diastolic blood pressure). Further application of TGFM to single-cell eQTL data from 9 cell types in peripheral blood mononuclear cells (PBMC), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs at PIP > 0.5-primarily for autoimmune disease and blood cell traits, including the biologically plausible example of CD52 in classical monocyte cells for Monocyte count. In conclusion, TGFM is a robust and powerful method for fine-mapping causal tissues and genes at disease-associated loci.

Estrogen-induced chromatin looping changes identify a subset of functional regulatory elements

Transcriptional enhancers can regulate individual or multiple genes through long-range three-dimensional (3D) genome interactions, and these interactions are commonly altered in cancer. Yet, the functional relationship between changes in 3D interactions associated with regulatory regions and differential gene expression appears context-dependent. In this study, we used HiChiP to capture changes in 3D genome interactions between active regulatory regions of endometrial cancer cells in response to estrogen treatment and uncovered significant differential long-range interactions that are strongly enriched for estrogen receptor α (ER) bound sites (ERBS). The ERBS anchoring differential loops with either a gene's promoter or distal regions were correlated with larger transcriptional responses to estrogen compared to ERBS not involved in differential interactions. To functionally test this observation, CRISPR-based Enhancer-i was used to deactivate specific ERBS, which revealed a wide range of effects on the transcriptional response to estrogen. However, these effects are only subtly and not significantly stronger for ERBS in differential loops. In addition, we observed an enrichment of 3D interactions between the promoters of estrogen up-regulated genes and found that looped promoters can work together cooperatively. Overall, our work suggests that changes in 3D genome structure upon estrogen treatment identify some functionally important regulatory regions; however, these changes aren't required for a transcriptional response to E2 in endometrial cancer cells.

The Capicua C1 Domain is Required for Full Activity of the CIC::DUX4 Fusion Oncoprotein

Rearrangements between genes can yield neomorphic fusions that drive oncogenesis. Fusion oncogenes are made up of fractional segments of the partner genes that comprise them, with each partner potentially contributing some of its own function to the nascent fusion oncoprotein. Clinically, fusion oncoproteins driving one diagnostic entity are typically clustered into a single molecular subset and are often treated a similar fashion. However, knowledge of where specific fusion breakpoints occur in partner genes, and the resulting retention of functional domains in the fusion, is an important determinant of fusion oncoprotein activity and may differ between patients. This study investigates this phenomena through the example of CIC::DUX4, a fusion between the transcriptional repressor capicua (CIC) and the double homeobox 4 gene (DUX4), which drives an aggressive subset of undifferentiated round cell sarcoma. Using a harmonized dataset of over 100 patient fusion breakpoints from the literature, we show that most bona fide CIC::DUX4 fusions retain the C1 domain, which is known to contribute to DNA binding by wild type CIC. Mechanistically, deletion or mutation of the C1 domain reduces, but does not eliminate, activation of CIC target genes by CIC::DUX4. We also find that expression of C1-deleted CIC::DUX4 is capable of exerting intermediate transformation-related phenotypes compared with those imparted by full-length CIC::DUX4, but was not sufficient for tumorigenesis in a subcutaneous mouse model. In summary, our results suggest a supercharging role for the C1 domain in the activity of CIC::DUX4.

TRIM32 inhibits Venezuelan Equine Encephalitis Virus Infection by targeting a late step in viral entry

Alphaviruses are mosquito borne RNA viruses that are a reemerging public health threat. Alphaviruses have a broad host range, and can cause diverse disease outcomes like arthritis, and encephalitis. The host ubiquitin proteasome system (UPS) plays critical roles in regulating cellular processes to control the infections with various viruses, including alphaviruses. Previous studies suggest alphaviruses hijack UPS for virus infection, but the molecular mechanisms remain poorly characterized. In addition, whether certain E3 ubiquitin ligases or deubiquitinases act as alphavirus restriction factors remains poorly understood. Here, we employed a cDNA expression screen to identify E3 ubiquitin ligase TRIM32 as a novel intrinsic restriction factor against alphavirus infection, including VEEV-TC83, SINV, and ONNV. Ectopic expression of TRIM32 reduces alphavirus infection, whereas depletion of TRIM32 with CRISPR-Cas9 increases infection. We demonstrate that TRIM32 inhibits alphaviruses through a mechanism that is independent of the TRIM32-STING-IFN axis. Combining reverse genetics and biochemical assays, we found that TRIM32 interferes with genome translation after membrane fusion, prior to replication of the incoming viral genome. Furthermore, our data indicate that the monoubiquitination of TRIM32 is important for its antiviral activity. Notably, we also show two TRIM32 pathogenic mutants R394H and D487N, related to Limb-girdle muscular dystrophy (LGMD), have a loss of antiviral activity against VEEV-TC83. Collectively, these results reveal that TRIM32 acts as a novel intrinsic restriction factor suppressing alphavirus infection and provides insights into the interaction between alphaviruses and the host UPS.

Phosphorothioate DNA modification by BREX Type 4 systems in the human gut microbiome

Among dozens of microbial DNA modifications regulating gene expression and host defense, phosphorothioation (PT) is the only known backbone modification, with sulfur inserted at a non-bridging oxygen by dnd and ssp gene families. Here we explored the distribution of PT genes in 13,663 human gut microbiome genomes, finding that 6.3% possessed dnd or ssp genes predominantly in Bacillota, Bacteroidota, and Pseudomonadota. This analysis uncovered several putative new PT synthesis systems, including Type 4 Bacteriophage Exclusion (BREX) brx genes, which were genetically validated in Bacteroides salyersiae. Mass spectrometric analysis of DNA from 226 gut microbiome isolates possessing dnd, ssp, and brx genes revealed 8 PT dinucleotide settings confirmed in 6 consensus sequences by PT-specific DNA sequencing. Genomic analysis showed PT enrichment in rRNA genes and depletion at gene boundaries. These results illustrate the power of the microbiome for discovering prokaryotic epigenetics and the widespread distribution of oxidation-sensitive PTs in gut microbes.

Next-Generation Modeling of Cancer Using Organoids

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be derived from many organs and cancer types and sites, encompassing both murine and human tissues. Importantly, they can be established from various stages during tumor evolution and recapitulate with high accuracy patient genomics and phenotypes in vitro, offering a platform for personalized medicine. Additionally, organoids are remarkably amendable for experimental manipulation. Taken together, these features make organoids a powerful tool with applications in basic cancer research and personalized medicine. Here, we will discuss the origins of organoid culture, applications in cancer research, and how cancer organoids can synergize with other models of cancer to drive basic discoveries as well as to translate these toward clinical solutions.

GAGA zinc finger transcription factor searches chromatin by 1D-3D facilitated diffusion

To elucidate how eukaryotic sequence-specific transcription factors (TFs) search for gene targets on chromatin, we used multi-color smFRET and single-particle imaging to track the diffusion of purified GAGA-Associated Factor (GAF) on DNA and nucleosomes. Monomeric GAF DNA-binding domain (DBD) bearing one zinc finger finds its cognate site by 1D or 3D diffusion on bare DNA and rapidly slides back-and-forth between naturally clustered motifs for seconds before escape. Multimeric, full-length GAF also finds clustered motifs on DNA by 1D-3D diffusion, but remains locked on target for longer periods. Nucleosome architecture effectively blocks GAF-DBD 1D-sliding into the histone core but favors retention of GAF-DBD when targeting solvent-exposed sites by 3D-diffusion. Despite the occlusive power of nucleosomes, 1D-3D facilitated diffusion enables GAF to effectively search for clustered cognate motifs in chromatin, providing a mechanism for navigation to nucleosome and nucleosome-free sites by a member of the largest TF family.

SETDB1 as a cancer target: challenges and perspectives in drug design

Genome stability is governed by chromatin structural dynamics, which modify DNA accessibility under the influence of intra- and inter-nucleosomal contacts, histone post-translational modifications (PTMs) and variations, besides the activity of ATP-dependent chromatin remodelers. These are the main ways by which chromatin dynamics are regulated and connected to nuclear processes, which when dysregulated can frequently be associated with most malignancies. Recently, functional crosstalk between histone modifications and chromatin remodeling has emerged as a critical regulatory method of transcriptional regulation during cell destiny choice. Therefore, improving therapeutic outcomes for patients by focusing on epigenetic targets dysregulated in malignancies should help prevent cancer cells from developing resistance to anticancer treatments. For this reason, SET domain bifurcated histone lysine methyltransferase 1 (SETDB1) has gained a lot of attention recently as a cancer target. SETDB1 is a histone lysine methyltransferase that plays an important role in marking euchromatic and heterochromatic regions. Hence, it promotes the silencing of tumor suppressor genes and contributes to carcinogenesis. Some studies revealed that SETDB1 was overexpressed in various human cancer types, which enhanced tumor growth and metastasis. Thus, SETDB1 appears to be an attractive epigenetic target for new cancer treatments. In this review, we have discussed the effects of its overexpression on the progression of tumors and the development of inhibitor drugs that specifically target this enzyme.

Wybutosine hypomodification of tRNAphe activates HERVK and impairs neuronal differentiation

We previously reported that loss of function of TYW1 led to cerebral palsy with severe intellectual disability through reduced neural proliferation. However, whether TYW1 loss affects neural differentiation is unknown. In this study, we first demonstrated that TYW1 loss blocked the formation of OHyW in tRNAphe and therefore affected the translation efficiency of UUU codon. Using the brain organoid model, we showed impaired neuron differentiation when TYW1 was depleted. Interestingly, retrotransposons were differentially regulated in TYW1-/- hESCs (human embryonic stem cells). In particular, one kind of human-specific endogenous retrovirus-K (HERVK/HML2), whose reactivation impaired human neurodevelopment, was significantly up-regulated in TYW1-/- hESCs. Consistently, a UUU codon-enriched protein, SMARCAD1, which was a key factor in controlling endogenous retroviruses, was reduced. Taken together, TYW1 loss leads to up-regulation of HERVK in hESCs by down-regulated SMARCAD1, thus impairing neuron differentiation.

Functional genomics implicates natural killer cells in the pathogenesis of ankylosing spondylitis

Objective

Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types mediating the genetic risk in AS using an unbiased functional genomics approach.

Methods

We integrated genome-wide association study (GWAS) data with epigenomic and transcriptomic datasets of human immune cells. To quantify enrichment of cell type-specific open chromatin or gene expression in AS risk loci, we used three published methods that have successfully identified relevant cell types in other diseases. We performed co-localization analyses between GWAS risk loci and genetic variants associated with gene expression (eQTL) to find putative target genes.

Results

Natural killer (NK) cell-specific open chromatin regions are significantly enriched in heritability for AS, compared to other immune cell types such as T cells, B cells, and monocytes. This finding was consistent between two AS GWAS. Using RNA-seq data, we validated that genes in AS risk loci are enriched in NK cell-specific gene expression. Using the human Space-Time Gut Cell Atlas, we also found significant upregulation of AS-associated genes predominantly in NK cells. Co-localization analysis revealed four AS risk loci affecting regulation of candidate target genes in NK cells: two known loci, ERAP1 and TNFRSF1A, and two under-studied loci, ENTR1 (aka SDCCAG3) and B3GNT2.

Conclusion

Our findings suggest that NK cells may play a crucial role in AS development and highlight four putative target genes for functional follow-up in NK cells.

Fast-spiking interneuron detonation drives high-fidelity inhibition in the olfactory bulb

Inhibitory circuits in the mammalian olfactory bulb (OB) dynamically reformat olfactory information as it propagates from peripheral receptors to downstream cortex. To gain mechanistic insight into how specific OB interneuron types support this sensory processing, we examine unitary synaptic interactions between excitatory mitral and tufted cells (MTCs), the OB projection cells, and a conserved population of anaxonic external plexiform layer interneurons (EPL-INs) using pair and quartet whole-cell recordings in acute mouse brain slices. Physiological, morphological, neurochemical, and synaptic analyses divide EPL-INs into distinct subtypes and reveal that parvalbumin-expressing fast-spiking EPL-INs (FSIs) perisomatically innervate MTCs with release-competent dendrites and synaptically detonate to mediate fast, short-latency recurrent and lateral inhibition. Sparse MTC synchronization supralinearly increases this high-fidelity inhibition, while sensory afferent activation combined with single-cell silencing reveals that individual FSIs account for a substantial fraction of total network-driven MTC lateral inhibition. OB output is thus powerfully shaped by detonation-driven high-fidelity perisomatic inhibition.

Transcranial Blood-Brain Barrier Opening in Alzheimer's Disease Patients Using a Portable Focused Ultrasound System with Real-Time 2-D Cavitation Mapping

Background

Focused ultrasound (FUS) in combination with microbubbles has recently shown great promise in facilitating blood-brain barrier (BBB) opening for drug delivery and immunotherapy in Alzheimer's disease (AD). However, it is currently limited to systems integrated within the MRI suites or requiring post-surgical implants, thus restricting its widespread clinical adoption. In this pilot study, we investigate the clinical safety and feasibility of a portable, non-invasive neuronavigation-guided FUS (NgFUS) system with integrated real-time 2-D microbubble cavitation mapping.

Methods

A phase 1 clinical study with mild to moderate AD patients (N=6) underwent a single session of microbubble-mediated NgFUS to induce transient BBB opening (BBBO). Microbubble activity under FUS was monitored with real-time 2-D cavitation maps and dosing to ensure the efficacy and safety of the NgFUS treatment. Post-operative MRI was used for BBB opening and closure confirmation as well as safety assessment. Changes in AD biomarker levels in both blood serum and extracellular vesicles (EVs) were evaluated, while changes in amyloid-beta (Aβ) load in the brain were assessed through 18F-Florbetapir PET.

Results

BBBO was achieved in 5 out of 6 subjects with an average volume of 983±626 mm3 following FUS at the right frontal lobe both in white and gray matter regions. The outpatient treatment was completed within 34.8±10.7 min. Cavitation dose significantly correlated with the BBBO volume (R2>0.9, N=4), demonstrating the portable NgFUS system's capability of predicting opening volumes. The cavitation maps co-localized closely with the BBBO location, representing the first report of real-time transcranial 2-D cavitation mapping in the human brain. Larger opening volumes correlated with increased levels of AD biomarkers, including Aβ42 (R2=0.74), Tau (R2=0.95), and P-Tau181 (R2=0.86), assayed in serum-derived EVs sampled 3 days after FUS (N=5). From PET scans, subjects showed a lower Aβ load increase in the treated frontal lobe region compared to the contralateral region. Reduction in asymmetry standardized uptake value ratios (SUVR) correlated with the cavitation dose (R2>0.9, N=3). Clinical changes in the mini-mental state examination over 6 months were within the expected range of cognitive decline with no additional changes observed as a result of FUS.

Conclusion

We showed the safety and feasibility of this cost-effective and time-efficient portable NgFUS treatment for BBBO in AD patients with the first demonstration of real-time 2-D cavitation mapping. The cavitation dose correlated with BBBO volume, a slowed increase in pathology, and serum detection of AD proteins. Our study highlights the potential for accessible FUS treatment in AD, with or without drug delivery.

Enhanced Detection and Genotyping of Disease-Associated Tandem Repeats Using HMMSTR and Targeted Long-Read Sequencing

Tandem repeat sequences comprise approximately 8% of the human genome and are linked to more than 50 neurodegenerative disorders. Accurate characterization of disease-associated repeat loci remains resource intensive and often lacks high resolution genotype calls. We introduce a multiplexed, targeted nanopore sequencing panel and HMMSTR, a sequence-based tandem repeat copy number caller. HMMSTR outperforms current signal- and sequence-based callers relative to two assemblies and we show it performs with high accuracy in heterozygous regions and at low read coverage. The flexible panel allows us to capture disease associated regions at an average coverage of >150x. Using these tools, we successfully characterize known or suspected repeat expansions in patient derived samples. In these samples we also identify unexpected expanded alleles at tandem repeat loci not previously associated with the underlying diagnosis. This genotyping approach for tandem repeat expansions is scalable, simple, flexible, and accurate, offering significant potential for diagnostic applications and investigation of expansion co-occurrence in neurodegenerative disorders.

Abstract Figure

Mechano-metabolism of adherent cells in 2D and 3D microenvironments

Cells regulate their shape and metabolic activity in response to the mechano-chemical properties of their microenvironment. To elucidate the impact of matrix stiffness and ligand density on a cell's bioenergetics, we developed a non-equilibrium, active chemo-mechanical model that accounts for mechanical energy of the cell and matrix, chemical energy from ATP hydrolysis, interfacial energy, and mechano-sensitive regulation of stress fiber assembly through signaling. By integrating the kinetics and energetics of these processes we introduce the concept of the metabolic potential of the cell that, when minimized, gives experimentally testable predictions of the cell contractility, shape, and the ATP consumption. Specifically, we show that MDA-MB-231 breast cancer cells in 3D collagen gels follow a spherical to spindle to spherical change in morphology with increasing matrix stiffness consistent with experimental observations. This biphasic transition in cell shape emerges from a competition between increased contractility accompanied by ATP hydrolysis enabled by mechano-sensitive signaling, which lowers the volumetric contribution to the metabolic potential of elongated cells and the interfacial energy which is lower for spherical shapes. On 2D hydrogels, our model predicts a hemispherical to spindle to disc shape transition with increasing gel stiffness. In both cases, we show that increasing matrix stiffness monotonically increases the cell's contractility as well as ATP consumption. Our model also predicts how the increased energy demand in stiffer microenvironments is met by AMPK activation, which is confirmed through experimental measurement of activated AMPK levels as a function of matrix stiffness carried out here in both 2D and 3D micro-environments. Further, model predictions of increased AMPK activation on stiffer micro-environments are found to correlate strongly with experimentally measured upregulation of mitochondrial potential, glucose uptake and ATP levels. The insights from our model can be used to understand mechanosensitive regulation of metabolism in physiological events such as metastasis and tumor progression during which cells experience dynamic changes in their microenvironment and metabolic state.

Context-specific functions of chromatin remodellers in development and disease

Chromatin remodellers were once thought to be highly redundant and nonspecific in their actions. However, recent human genetic studies demonstrate remarkable biological specificity and dosage sensitivity of the thirty-two adenosine triphosphate (ATP)-dependent chromatin remodellers encoded in the human genome. Mutations in remodellers produce many human developmental disorders and cancers, motivating efforts to investigate their distinct functions in biologically relevant settings. Exquisitely specific biological functions seem to be an emergent property in mammals, and in many cases are based on the combinatorial assembly of subunits and the generation of stable, composite surfaces. Critical interactions between remodelling complex subunits, the nucleosome and other transcriptional regulators are now being defined from structural and biochemical studies. In addition, in vivo analyses of remodellers at relevant genetic loci have provided minute-by-minute insights into their dynamics. These studies are proposing new models for the determinants of remodeller localization and function on chromatin.

Chemical manipulation of m1A mediates its detection in human tRNA

N 1-methyl adenosine (m1A) is a widespread RNA modification present in tRNA, rRNA, and mRNA. m1A modification sites in tRNAs are evolutionarily conserved and its formation on tRNA is catalyzed by methyltransferase TRMT61A and TRMT6 complex. m1A promotes translation initiation and elongation. Due to its positive charge under physiological conditions, m1A can notably modulate RNA structure. It also blocks Watson-Crick-Franklin base-pairing and causes mutation and truncation during reverse transcription. Several misincorporation-based high-throughput sequencing methods have been developed to sequence m1A. In this study, we introduce a reduction-based m1A sequencing (red-m1A-seq). We report that NaBH4 reduction of m1A can improve the mutation and readthrough rates using commercially available RT enzymes to give a better positive signature, while alkaline-catalyzed Dimroth rearrangement can efficiently convert m1A to m6A to provide good controls, allowing the detection of m1A with higher sensitivity and accuracy. We applied red-m1A-seq to sequence human small RNA, and we not only detected all the previously reported tRNA m1A sites, but also new m1A sites in mt-tRNAAsn-GTT and 5.8S rRNA.

Isogenic hiPSC models of Turner syndrome development reveal shared roles of inactive X and Y in the human cranial neural crest network

Modeling the developmental etiology of viable human aneuploidy can be challenging in rodents due to syntenic boundaries, or primate-specific biology. In humans, monosomy-X (45,X) causes Turner syndrome (TS), altering craniofacial, skeletal, endocrine, and cardiovascular development, which in contrast remain unaffected in 39,X-mice. To learn how human monosomy-X may impact early embryonic development, we turned to human 45,X and isogenic euploid induced pluripotent stem cells (hiPSCs) from male and female mosaic donors. Because neural crest (NC) derived cell types are hypothesized to underpin craniofacial and cardiovascular changes in TS, we performed a highly-powered differential expression study on hiPSC-derived anterior neural crest cells (NCCs). Across three independent isogenic panels, 45,X NCCs show impaired acquisition of PAX7+SOX10+ markers, and disrupted expression of other NCC-specific genes, relative to their isogenic euploid controls. In particular, 45,X NCCs increase cholesterol biosynthesis genes while reducing transcripts that feature 5' terminal oligopyrimidine (TOP) motifs, including those of ribosomal protein and nuclear-encoded mitochondrial genes. Such metabolic pathways are also over-represented in weighted co-expression gene modules that are preserved in monogenic neurocristopathy. Importantly, these gene modules are also significantly enriched in 28% of all TS-associated terms of the human phenotype ontology. Our analysis identifies specific sex-linked genes that are expressed from two copies in euploid males and females alike and qualify as candidate haploinsufficient drivers of TS phenotypes in NC-derived lineages. This study demonstrates that isogenic hiPSC-derived NCC panels representing monosomy-X can serve as a powerful model of early NC development in TS and inform new hypotheses towards its etiology.

Proteasome hyperactivation rewires the proteome enhancing stress resistance, proteostasis, lipid metabolism and ERAD in C. elegans

Proteasome dysfunction is implicated in the pathogenesis of neurodegenerative diseases and age-related proteinopathies. Using a C. elegans model, we demonstrate that 20S proteasome hyperactivation, facilitated by 20S gate-opening, accelerates the targeting of intrinsically disordered proteins. This leads to increased protein synthesis, extensive rewiring of the proteome and transcriptome, enhanced oxidative stress defense, accelerated lipid metabolism, and peroxisome proliferation. It also promotes ER-associated degradation (ERAD) of aggregation-prone proteins, such as alpha-1 antitrypsin (ATZ) and various lipoproteins. Notably, our results reveal that 20S proteasome hyperactivation suggests a novel role in ERAD with broad implications for proteostasis-related disorders, simultaneously affecting lipid homeostasis and peroxisome proliferation. Furthermore, the enhanced cellular capacity to mitigate proteostasis challenges, alongside unanticipated acceleration of lipid metabolism is expected to contribute to the longevity phenotype of this mutant. Remarkably, the mechanism of longevity induced by 20S gate opening appears unique, independent of known longevity and stress-resistance pathways. These results support the therapeutic potential of 20S proteasome activation in mitigating proteostasis-related disorders broadly and provide new insights into the complex interplay between proteasome activity, cellular health, and aging.

Dynamic neuroinflammatory profiles predict Alzheimer's disease pathology in microglia-containing cerebral organoids

Neuroinflammation and the underlying dysregulated immune responses of microglia actively contribute to the progression and, likely, the initiation of Alzheimer's disease (AD). Fine-tuned therapeutic modulation of immune dysfunction to ameliorate disease cannot be achieved without the characterization of diverse microglial states that initiate unique, and sometimes contradictory, immune responses that evolve over time in chronic inflammatory environments. Because of the functional differences between human and murine microglia, untangling distinct, disease-relevant reactive states and their corresponding effects on pathology or neuronal health may not be possible without the use of human cells. In order to profile shifting microglial states in early AD and identify microglia-specific drivers of disease, we differentiated human induced pluripotent stem cells (iPSCs) carrying a familial AD PSEN2 mutation or its isogenic control into cerebral organoids and quantified the changes in cytokine concentrations over time with Luminex XMAP technology. We used partial least squares (PLS) modeling to build cytokine signatures predictive of disease and age to identify key differential patterns of cytokine expression that inform the overall organoid immune milieu and quantified the corresponding changes in protein pathology. AD organoids exhibited an overall reduction in cytokine secretion after an initial amplified immune response. We demonstrate that reduced synapse density observed in the AD organoids is prevented with microglial depletion. Crucially, these differential effects of dysregulated immune signaling occurred without the accumulation of pathological proteins. In this study, we used microglia-containing AD organoids to quantitatively characterize an evolving immune milieu, made up of a diverse of collection of activation patterns and immune responses, to identify how a dynamic, overall neuroinflammatory state negatively impacts neuronal health and the cell-specific contribution of microglia.

CHANGE-seq-BE enables simultaneously sensitive and unbiased in vitro profiling of base editor genome-wide activity

Base editors ( BE ) enable programmable conversion of nucleotides in genomic DNA without double-stranded breaks and have substantial promise to become new transformative genome editing medicines. Sensitive and unbiased detection of base editor off-target effects is important for identifying safety risks unique to base editors and translation to human therapeutics, as well as accurate use in life sciences research. However, current methods for understanding the global activities of base editors have limitations in terms of sensitivity or bias. Here we present CHANGE-seq-BE, a novel method to directly assess the off-target profile of base editors that is simultaneously sensitive and unbiased. CHANGE-seq-BE is based on the principle of selective sequencing of adenine base editor modified genomic DNA in vitro , and provides an accessible, rapid, and comprehensive method for identifying genome-wide off-target mutations of base editors.

Illuminating the Dark Cancer Phosphoproteome Through a Machine-Learned Co-Regulation Map of 26,280 Phosphosites

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, but limited knowledge about the regulation and function of most phosphosites restricts our ability to extract meaningful biological insights from phosphoproteomics data. To address this, we combine machine learning and phosphoproteomic data from 1,195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network mapping the co-regulation of 26,280 phosphosites. Integrating network features from CoPheeMap into a machine learning model, CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA reveals 24,015 associations between 9,399 phosphosites and 104 serine/threonine kinases, including many unannotated phosphosites and under-studied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. By applying CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and cancer-associated phosphosites, we demonstrate the effectiveness of these tools in systematically illuminating phosphosites of interest, revealing dysregulated signaling processes in human cancer, and identifying under-studied kinases as putative therapeutic targets.

Mutation of the SWI/SNF complex component Smarce1 decreases nucleosome stability in embryonic stem cells and impairs differentiation

The SWI/SNF chromatin remodeling complex consists of more than ten component proteins that form a large protein complex of >1 MDa. The catalytic proteins Smarca4 or Smarca2 work in concert with the component proteins to form a chromatin platform suitable for transcriptional regulation. However, the mechanism by which each component protein works synergistically with the catalytic proteins remains largely unknown. Here, we report on the function of Smarce1, a component of the SWI/SNF complex, through the phenotypic analysis of homozygous mutant embryonic stem cells (ESCs). Disruption of Smarce1 induced the dissociation of other complex components from the SWI/SNF complex. Histone binding to DNA was loosened in homozygous mutant ESCs, indicating that disruption of Smarce1 decreased nucleosome stability. Sucrose gradient sedimentation analysis suggested that there was an ectopic genomic distribution of the SWI/SNF complex upon disruption of Smarce1, accounting for the misregulation of chromatin conformations. Unstable nucleosomes remained during ESC differentiation, impairing the heterochromatin formation that is characteristic of the differentiation process. These results suggest that Smarce1 guides the SWI/SNF complex to the appropriate genomic regions to generate chromatin structures adequate for transcriptional regulation.

The role of Smarcad1 in retroviral repression in mouse embryonic stem cells

BACKGROUND

Moloney murine leukemia virus (MLV) replication is suppressed in mouse embryonic stem cells (ESCs) by the Trim28-SETDB1 complex. The chromatin remodeler Smarcad1 interacts with Trim28 and was suggested to allow the deposition of the histone variant H3.3. However, the role of Trim28, H3.3, and Smarcad1 in MLV repression in ESCs still needs to be fully understood.

RESULTS

In this study, we used MLV to explore the role of Smarcad1 in retroviral silencing in ESCs. We show that Smarcad1 is immediately recruited to the MLV provirus. Based on the repression dynamics of a GFP-reporter MLV, our findings suggest that Smarcad1 plays a critical role in the establishment and maintenance of MLV repression, as well as other Trim28-targeted genomic loci. Furthermore, Smarcad1 is important for stabilizing and strengthening Trim28 binding to the provirus over time, and its presence around the provirus is needed for proper deposition of H3.3 on the provirus. Surprisingly, the combined depletion of Smarcad1 and Trim28 results in enhanced MLV derepression, suggesting that these two proteins may also function independently to maintain repressive chromatin states.

CONCLUSIONS

Overall, the results of this study provide evidence for the crucial role of Smarcad1 in the silencing of retroviral elements in embryonic stem cells. Further research is needed to fully understand how Smarcad1 and Trim28 cooperate and their implications for gene expression and genomic stability.

Up-regulation of cholesterol synthesis by lysosomal defects requires a functional mitochondrial respiratory chain

Mitochondria and lysosomes are two organelles that carry out both signaling and metabolic roles in the cells. Recent evidence has shown that mitochondria and lysosomes are dependent on one another, as primary defects in one cause secondary defects in the other. Nevertheless, the signaling consequences of primary mitochondrial malfunction and of primary lysosomal defects are not similar, despite in both cases there are impairments of mitochondria and of lysosomes. Here, we used RNA sequencing to obtain transcriptomes from cells with primary mitochondrial or lysosomal defects, to identify what are the global cellular consequences that are associated with malfunction of mitochondria or lysosomes. We used these data to determine what are the pathways that are affected by defects in both organelles, which revealed a prominent role for the cholesterol synthesis pathway. This pathway is transcriptionally up-regulated in cellular and mouse models of lysosomal defects and is transcriptionally down-regulated in cellular and mouse models of mitochondrial defects. We identified a role for post-transcriptional regulation of the transcription factor SREBF1, a master regulator of cholesterol and lipid biosynthesis, in models of mitochondrial respiratory chain deficiency. Furthermore, the retention of Ca 2+ in the lysosomes of cells with mitochondrial respiratory chain defects contributes to the differential regulation of the cholesterol synthesis pathway in the mitochondrial and lysosomal defects tested. Finally, we verified in vivo , using models of mitochondria-associated diseases in C. elegans , that normalization of lysosomal Ca 2+ levels results in partial rescue of the developmental arrest induced by the respiratory chain deficiency.

Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures

Sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed along the auditory pathway. Here, we compared the neural representation of sound textures in the inferior colliculus (IC) and auditory cortex (AC) of anesthetized female rats. We recorded responses to texture morph stimuli that gradually add statistical features of increasingly higher complexity. For each texture, several different exemplars were synthesized using different random seeds. An analysis of transient and ongoing multiunit responses showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent. In contrast, only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of "texture type tuning" in the IC, but the same was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses, classification performance remained consistently very low. These results argue against the idea that AC neurons encode sound type via an overt sensitivity in neural firing rate to fine-grain spectral and temporal statistical features.

Pan-cancer molecular signatures connecting aspartate transaminase (AST) to cancer prognosis, metabolic and immune signatures

Background

Serum aspartate transaminase (sAST) level is used routinely in conjunction with other clinical assays to assess liver health and disease. Increasing evidence suggests that sAST is associated with all-cause mortality and has prognostic value in several cancers, including gastrointestinal and urothelial cancers. Here, we undertake a systems approach to unravel molecular connections between AST and cancer prognosis, metabolism, and immune signatures at the transcriptomic and proteomic levels.

Methods

We mined public gene expression data across multiple normal and cancerous tissues using the Genotype Tissue Expression (GTEX) resource and The Cancer Genome Atlas (TCGA) to assess the expression of genes encoding AST isoenzymes (GOT1 and GOT2) and their association with disease prognosis and immune infiltration signatures across multiple tumors. We examined the associations between AST and previously reported pan-cancer molecular subtypes characterized by distinct metabolic and immune signatures. We analyzed human protein-protein interaction networks for interactions between GOT1 and GOT2 with cancer-associated proteins. Using public databases and protein-protein interaction networks, we determined whether the subset of proteins that interact with AST (GOT1 and GOT2 interactomes) are enriched with proteins associated with specific diseases, miRNAs and transcription factors.

Results

We show that AST transcript isoforms (GOT1 and GOT2) are expressed across a wide range of normal tissues. AST isoforms are upregulated in tumors of the breast, lung, uterus, and thymus relative to normal tissues but downregulated in tumors of the liver, colon, brain, kidney and skeletal sarcomas. At the proteomic level, we find that the expression of AST is associated with distinct pan-cancer molecular subtypes with an enrichment of specific metabolic and immune signatures. Based on human protein-protein interaction data, AST physically interacts with multiple proteins involved in tumor initiation, suppression, progression, and treatment. We find enrichments in the AST interactomes for proteins associated with liver and lung cancer and dermatologic diseases. At the regulatory level, the GOT1 interactome is enriched with the targets of cancer-associated miRNAs, specifically mir34a - a promising cancer therapeutic, while the GOT2 interactome is enriched with proteins that interact with cancer-associated transcription factors.

Conclusions

Our findings suggest that perturbations in the levels of AST within specific tissues reflect pathophysiological changes beyond tissue damage and have implications for cancer metabolism, immune infiltration, prognosis, and treatment personalization.

Rare SNP in the HELB gene interferes with RPA interaction and cellular function of HELB

HELB is a human helicase involved in initiation of DNA replication, the replication stress response, and regulation of double-strand DNA break repair. rs75770066 is a rare SNP in the HELB gene that affects age at natural menopause. rs75770066 results in a D506G substitution in an acidic patch within the 1A domain of the helicase that is known to interact with RPA. We found that this amino acid change dramatically impairs the cellular function of HELB. D506G-HELB exhibits impaired interaction with RPA, which likely results in the effects of rs75770066 as this reduces recruitment of HELB to sites of DNA damage. Reduced recruitment of D506G-HELB to double-strand DNA breaks and the concomitant increase in homologous recombination likely alters the levels of meiotic recombination, which affects the viability of gametes. Because menopause occurs when oocyte levels drop below a minimum threshold, altered repair of meiotic double-stranded DNA breaks has the potential to directly affect the age at natural menopause.

Domain coupling in activation of a family C GPCR

The G protein-coupled metabotropic glutamate receptors form homodimers and heterodimers with highly diverse responses to glutamate and varying physiological function. The molecular basis for this diversity remains poorly delineated. We employ molecular dynamics, single-molecule spectroscopy, and hydrogen-deuterium exchange to dissect the pathway of activation triggered by glutamate. We find that activation entails multiple loosely coupled steps and identify a novel pre-active intermediate whose transition to the active state forms dimer interactions that set signaling efficacy. Such subunit interactions generate functional diversity that differs across homodimers and heterodimers. The agonist-bound receptor is remarkably dynamic, with low occupancy of G protein-coupling conformations, providing considerable headroom for modulation of the landscape by allosteric ligands. Sites of sequence diversity within the dimerization interface and diverse coupling between activation rearrangements may contribute to precise decoding of glutamate signals and transients over broad spatial and temporal scales.

Constraining models of dominance for nonsynonymous mutations in the human genome

Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h=0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.

Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories

Spatial periodicity in grid cell firing has been interpreted as a neural metric for space providing animals with a coordinate system in navigating physical and mental spaces. However, the specific computational problem being solved by grid cells has remained elusive. Here, we provide mathematical proof that spatial periodicity in grid cell firing is the only possible solution to a neural sequence code of 2-D trajectories and that the hexagonal firing pattern of grid cells is the most parsimonious solution to such a sequence code. We thereby provide a teleological cause for the existence of grid cells and reveal the underlying nature of the global geometric organization in grid maps as a direct consequence of a simple local sequence code. A sequence code by grid cells provides intuitive explanations for many previously puzzling experimental observations and may transform our thinking about grid cells.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

Novel syndromic neurodevelopmental disorder caused by de novo deletion of CHASERR, a long noncoding RNA

Genes encoding long non-coding RNAs (lncRNAs) comprise a large fraction of the human genome, yet haploinsufficiency of a lncRNA has not been shown to cause a Mendelian disease. CHASERR is a highly conserved human lncRNA adjacent to CHD2-a coding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here we report three unrelated individuals each harboring an ultra-rare heterozygous de novo deletion in the CHASERR locus. We report similarities in severe developmental delay, facial dysmorphisms, and cerebral dysmyelination in these individuals, distinguishing them from the phenotypic spectrum of CHD2 haploinsufficiency. We demonstrate reduced CHASERR mRNA expression and corresponding increased CHD2 mRNA and protein in whole blood and patient-derived cell lines-specifically increased expression of the CHD2 allele in cis with the CHASERR deletion, as predicted from a prior mouse model of Chaserr haploinsufficiency. We show for the first time that de novo structural variants facilitated by Alu-mediated non-allelic homologous recombination led to deletion of a non-coding element (the lncRNA CHASERR) to cause a rare syndromic neurodevelopmental disorder. We also demonstrate that CHD2 has bidirectional dosage sensitivity in human disease. This work highlights the need to carefully evaluate other lncRNAs, particularly those upstream of genes associated with Mendelian disorders.

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements

The challenge of systematically modifying and optimizing regulatory elements for precise gene expression control is central to modern genomics and synthetic biology. Advancements in generative AI have paved the way for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significant potential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metrics to ensure they retain properties of endogenous sequences: transcription factor binding site composition, potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusion to activate gene expression in different cell contexts using state-of-the-art prediction models. Our results demonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biology and precision gene therapy.

HIRA vs. DAXX: the two axes shaping the histone H3.3 landscape

H3.3, the most common replacement variant for histone H3, has emerged as an important player in chromatin dynamics for controlling gene expression and genome integrity. While replicative variants H3.1 and H3.2 are primarily incorporated into nucleosomes during DNA synthesis, H3.3 is under the control of H3.3-specific histone chaperones for spatiotemporal incorporation throughout the cell cycle. Over the years, there has been progress in understanding the mechanisms by which H3.3 affects domain structure and function. Furthermore, H3.3 distribution and relative abundance profoundly impact cellular identity and plasticity during normal development and pathogenesis. Recurrent mutations in H3.3 and its chaperones have been identified in neoplastic transformation and developmental disorders, providing new insights into chromatin biology and disease. Here, we review recent findings emphasizing how two distinct histone chaperones, HIRA and DAXX, take part in the spatial and temporal distribution of H3.3 in different chromatin domains and ultimately achieve dynamic control of chromatin organization and function. Elucidating the H3.3 deposition pathways from the available histone pool will open new avenues for understanding the mechanisms by which H3.3 epigenetically regulates gene expression and its impact on cellular integrity and pathogenesis.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Lateralized Functional Connectivity of the Sensorimotor Cortex and its Variations During Complex Visuomotor Tasks

Previous studies have shown that the left hemisphere dominates motor function, often observed through homotopic activation measurements. Using a functional connectivity approach, this study investigated the lateralization of the sensorimotor cortex during handwriting and drawing, two complex visuomotor tasks with varying contextual demands. We found that both left- and right-lateralized connectivity in the primary motor cortex (M1), dorsal premotor cortex (PMd), somatosensory cortex, and visual regions were evident in adults (males and females), primarily in an interhemispheric integrative fashion. Critically, these lateralization tendencies remained highly invariant across task contexts, representing a task-invariant neural architecture for encoding fundamental motor programs consistently implemented in different task contexts. Additionally, the PMd exhibited a slight variation in lateralization degree between task contexts, reflecting the ability of the high-order motor system to adapt to varying task demands. However, connectivity-based lateralization of the sensorimotor cortex was not detected in 10-year-old children (males and females), suggesting that the maturation of connectivity-based lateralization requires prolonged development. In summary, this study demonstrates both task-invariant and task-sensitive connectivity lateralization in sensorimotor cortices that support the resilience and adaptability of skilled visuomotor performance. These findings align with the hierarchical organization of the motor system and underscore the significance of the functional connectivity-based approach in studying functional lateralization.

BDNF signaling requires Matrix Metalloproteinase-9 during structural synaptic plasticity

Synaptic plasticity underlies learning and memory processes as well as contributes, in its aberrant form, to neuropsychiatric disorders. One of its major forms is structural long-term potentiation (sLTP), an activity-dependent growth of dendritic spines that harbor excitatory synapses. The process depends on the release of brain-derived neurotrophic factor (BDNF), and activation of its receptor, TrkB. Matrix metalloproteinase-9 (MMP-9), an extracellular protease is essential for many forms of neuronal plasticity engaged in physiological as well as pathological processes. Here, we utilized two-photon microscopy and two-photon glutamate uncaging to demonstrate that MMP-9 activity is essential for sLTP and is rapidly (~seconds) released from dendritic spines in response to synaptic stimulation. Moreover, we show that either chemical or genetic inhibition of MMP-9 impairs TrkB activation, as measured by fluorescence lifetime imaging microscopy of FRET sensor. Furthermore, we provide evidence for a cell-free cleavage of proBDNF into mature BDNF by MMP-9. Our findings point to the autocrine mechanism of action of MMP-9 through BDNF maturation and TrkB activation during sLTP.

Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy

Background

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).

Method

In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.

Results

Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP.

Conclusions

Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Self-organizing glycolytic waves fuel cell migration and cancer progression

Glycolysis has traditionally been thought to take place in the cytosol but we observed the enrichment of glycolytic enzymes in propagating waves of the cell cortex in human epithelial cells. These waves reflect excitable Ras/PI3K signal transduction and F-actin/actomyosin networks that drive cellular protrusions, suggesting that localized glycolysis at the cortex provides ATP for cell morphological events such as migration, phagocytosis, and cytokinesis. Perturbations that altered cortical waves caused corresponding changes in enzyme localization and ATP production whereas synthetic recruitment of glycolytic enzymes to the cell cortex enhanced cell spreading and motility. Interestingly, the cortical waves and ATP levels were positively correlated with the metastatic potential of cancer cells. The coordinated signal transduction, cytoskeletal, and glycolytic waves in cancer cells may explain their increased motility and their greater reliance on glycolysis, often referred to as the Warburg effect.

Multi-omic integration of microbiome data for identifying disease-associated modules

The human gut microbiome is a complex ecosystem with profound implications for health and disease. This recognition has led to a surge in multi-omic microbiome studies, employing various molecular assays to elucidate the microbiome's role in diseases across multiple functional layers. However, despite the clear value of these multi-omic datasets, rigorous integrative analysis of such data poses significant challenges, hindering a comprehensive understanding of microbiome-disease interactions. Perhaps most notably, multiple approaches, including univariate and multivariate analyses, as well as machine learning, have been applied to such data to identify disease-associated markers, namely, specific features (e.g., species, pathways, metabolites) that are significantly altered in disease state. These methods, however, often yield extensive lists of features associated with the disease without effectively capturing the multi-layered structure of multi-omic data or offering clear, interpretable hypotheses about underlying microbiome-disease mechanisms. Here, we address this challenge by introducing MintTea - an intermediate integration-based method for analyzing multi-omic microbiome data. MintTea combines a canonical correlation analysis (CCA) extension, consensus analysis, and an evaluation protocol to robustly identify disease-associated multi-omic modules. Each such module consists of a set of features from the various omics that both shift in concord, and collectively associate with the disease. Applying MintTea to diverse case-control cohorts with multi-omic data, we show that this framework is able to capture modules with high predictive power for disease, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome (MS) study, we found a MS-associated module comprising of a highly correlated cluster of serum glutamate- and TCA cycle-related metabolites, as well as bacterial species previously implicated in insulin resistance. In another cohort, we identified a module associated with late-stage colorectal cancer, featuring Peptostreptococcus and Gemella species and several fecal amino acids, in agreement with these species' reported role in the metabolism of these amino acids and their coordinated increase in abundance during disease development. Finally, comparing modules identified in different datasets, we detected multiple significant overlaps, suggesting common interactions between microbiome features. Combined, this work serves as a proof of concept for the potential benefits of advanced integration methods in generating integrated multi-omic hypotheses underlying microbiome-disease interactions and a promising avenue for researchers seeking systems-level insights into coherent mechanisms governing microbiome-related diseases.

Regulation of endogenous retroviruses in murine embryonic stem cells and early embryos

Endogenous retroviruses (ERVs) are important components of transposable elements that constitute ∼40% of the mouse genome. ERVs exhibit dynamic expression patterns during early embryonic development and are engaged in numerous biological processes. Therefore, ERV expression must be closely monitored in cells. Most studies have focused on the regulation of ERV expression in mouse embryonic stem cells (ESCs) and during early embryonic development. This review touches on the classification, expression, and functions of ERVs in mouse ESCs and early embryos and mainly discusses ERV modulation strategies from the perspectives of transcription, epigenetic modification, nucleosome/chromatin assembly, and post-transcriptional control.

Non-Degenerate Two-Photon Imaging of Deep Rodent Cortex using Indocyanine Green in the water absorption window

We present a novel approach for deep vascular imaging in rodent cortex at excitation wavelengths susceptible to water absorption using two-photon microscopy with photons of dissimilar wavelengths. We demonstrate that non-degenerate two-photon excitation (ND-2PE) enables imaging in the water absorption window from 1400-1550 nm using two synchronized excitation sources at 1300 nm and 1600 nm that straddle the absorption window. We explore the brightness spectra of indocyanine green (ICG) and assess its suitability for imaging in the water absorption window. Further, we demonstrate in vivo imaging of the rodent cortex vascular structure up to 1.2 mm using ND-2PE. Lastly, a comparative analysis of ND-2PE at 1435 nm and single-wavelength, two-photon imaging at 1300 nm and 1435 nm is presented. Our work extends the excitation range for fluorescent dyes to include water absorption regimes and underscores the feasibility of deep two-photon imaging at these wavelengths.

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of ten different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

mixWAS: An efficient distributed algorithm for mixed-outcomes genome-wide association studies

Genome-wide association studies (GWAS) have been instrumental in identifying genetic associations for various diseases and traits. However, uncovering genetic underpinnings among traits beyond univariate phenotype associations remains a challenge. Multi-phenotype associations (MPA), or genetic pleiotropy, offer important insights into shared genes and pathways among traits, enhancing our understanding of genetic architectures of complex diseases. GWAS of biobank-linked electronic health record (EHR) data are increasingly being utilized to identify MPA among various traits and diseases. However, methodologies that can efficiently take advantage of distributed EHR to detect MPA are still lacking. Here, we introduce mixWAS, a novel algorithm that efficiently and losslessly integrates multiple EHRs via summary statistics, allowing the detection of MPA among mixed phenotypes while accounting for heterogeneities across EHRs. Simulations demonstrate that mixWAS outperforms the widely used MPA detection method, Phenome-wide association study (PheWAS), across diverse scenarios. Applying mixWAS to data from seven EHRs in the US, we identified 4,534 MPA among blood lipids, BMI, and circulatory diseases. Validation in an independent EHR data from UK confirmed 97.7% of the associations. mixWAS fundamentally improves the detection of MPA and is available as a free, open-source software.