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Ali, M.

Publications and source records attributed to Ali, M..

At least 55 records · Page 3Linked to original sources

Developmental regulation of Drosophila dosage compensation in a 3D genome context

Chromosomal dosage compensation (DC) restores the expression balance of X chromosome between sexes, and is realised in Drosophila by the coordination of enriched X-linked PionX, HAS sequence elements and 1.6883F satellites, resulting in doubling the transcription of X-linked genes in males. We hypothesize that DC must be finely tuned during development and ask what are the underlying molecular mechanisms in this work. To inspect this, we collect new and published histone modification and 3D genome data of sexed samples from embryos to adults of Drosophila. We find that at least 30% of the Drosophila genes are bound by the DC complex or characteristic H4K16ac modifications specifically in only one or more tissues, and they show a higher H3K27me3 binding level than the rest DC genes constitutively compensated throughout development. The chrX harbors developmentally increasing long-range contacts (LRCs) relative to autosomes, and specifically in males. Integrative analyses with DC genes and regulatory sequences show that HAS and housekeeping genes preferentially located at the chromatin domain boundaries form stable LRCs. While PionXs and 1.6883F only form LRCs with the developmentally regulated DC genes in embryos and testes. Our results indicate that the Drosophila male chrX is characterised by two types of stable and developmentally regulated LRCs coordinating the dosage compensation to the different functional background of genes.

evolutionary biology↗

Future flooding tolerant rice germplasm: resilience afforded beyond Sub1A gene

Developing high-yielding, flood-tolerant rice varieties is essential for enhancing productivity and livelihoods in flood-prone ecologies. We explored genetic avenues beyond the well-known SUB1A gene to improve flood resilience in rice. We screened a collection of 6,274 elite genotypes from IRRIs germplasm repository for submergence and stagnant flooding tolerance over multiple seasons and years. This rigorous screening identified 89 outstanding elite genotypes, among which thirty-seven exhibited high submergence tolerance, surpassing the survival rate of SUB1A introgression genotypes by 40-50%. Thirty-five genotypes showed significant tolerance to stagnant flooding, and 17 demonstrated dual tolerance capabilities, highlighting their adaptability to varying flood conditions. The genotypes identified have a broader genetic diversity and harbor 86 key QTLs and genes related to traits such as grain quality, grain yield, herbicide resistance, and various biotic and abiotic traits, highlighting the richness of the identified elite collection. Besides germplasm, we introduce an innovative breeding approach called Transition from Trait to Environment (TTE). TTE leverages a parental pool of high-performing genotypes with complete submergence tolerance to drive population improvement and enable genomic selection in the flood breeding program. Our approach of TTE achieved a remarkable 65% increase in genetic gain for submergence tolerance, with the resulting fixed breeding genotypes demonstrating exceptional performance in flood-prone environments of India and Bangladesh. The elite genotypes identified herein represent invaluable genetic resources for the global rice research community. By adopting the TTE approach, which is trait agonistic, we establish a robust framework for developing more resilient genotypes using advanced breeding tools. Plain Language SummaryTo address climate challenges, an urgent focus is necessary to identify and develop flood-tolerant rice varieties, particularly for flood-prone ecosystems across Asia and Africa. We screened 6,274 elite genotypes from IRRIs germplasm and identified 89 promising lines with improved tolerance to submergence and stagnant flooding. Among these, 37 demonstrated 40-50% greater submergence tolerance than SUB1A introgression lines, 35 exhibited stagnant flooding tolerance, and 17 showed dual tolerance. These genotypes contain 86 key QTLs and genes associated with yield, grain quality, and biotic and abiotic tolerance traits. A new breeding strategy, the Transition from Trait to Environment (TTE) approach, was developed. We achieved a genetic gain of 65% for submergence tolerance in rice using this method. The newly identified germplasm provides invaluable genetic resources for the global rice research community to develop flood-tolerant rice genotypes. Core ideas The SUB1A gene, enabling rice to survive underwater for 14 days, marked a significant breakthrough. We have identified elite genotypes with submergence tolerance significantly surpassing the SUB1A gene-mediated tolerance. The diverse elite genotypes identified harbor 86 key genes and QTLs that affect various traits positively. Developed a unique breeding strategy for implementing population improvement in challenging environments. The new breeding strategy demonstrated a genetic gain of 65% for submergence tolerance.

plant biology↗

Advancing White Blood Cell Detection: A Multi-Domain Dataset for Morphological Analysis and Addressing Sparse Annotation Challenges

Leukemia is 10th most frequently diagnosed cancer and one of the leading causes of cancer-related deaths worldwide. Realistic analysis of Leukemia requires White Blook Cells (WBC) localization, classification, and morphological assessment. Despite deep learning advances in medical imaging, leukemia analysis lacks a large, diverse multi-task dataset, while existing small datasets lack domain diversity, limiting real-world applicability. To overcome dataset challenges, we present a large-scale WBC dataset named Large Leukemia Dataset (LLD) and novel methods for detecting WBC with their attributes. Our contribution here is threefold. First, we present a large-scale Leukemia dataset collected through Peripheral Blood Films (PBF) from several patients, through multiple microscopes, multi-cameras, and multi-magnification. To enhance diagnosis explainability and medical expert acceptance, each leukemia cell is annotated at 100x with 7 morphological attributes, ranging from Cell Size to Nuclear Shape. Secondly, we propose a multi-task model that not only detects WBCs but also predicts their attributes, providing an interpretable and clinically meaningful solution. Third, we propose a method for WBC detection with attribute analysis using sparse annotations. This approach reduces the annotation burden on hematologists, requiring them to mark only a small area within the field of view. Our method enables the model to leverage the entire field of view rather than just the annotated regions, enhancing learning efficiency and diagnostic accuracy. From diagnosis explainability to overcoming domain-shift challenges, presented datasets could be used for many challenging aspects of microscopic image analysis. The datasets, code, and demo are available at: https://im.itu.edu.pk/sparse-leukemiaattri/.

pathology↗

ANKZF1 helps to eliminate the stress-damaged mitochondria by LC3-mediated mitophagy

Mitochondria, the double membrane-bound organelles of endosymbiotic origin, are crucial centers for cellular energy production and several essential metabolic pathways. Recent studies reveal that mitochondria become dysfunctional following numerous cellular stresses, and during pathologies, demanding an extensive investigation of mitochondrial turnover mechanisms. Apart from the specific response pathways to tackle different stresses, mitophagy or degradation of mitochondria by autophagy is a critical quality control mechanism that clears irreversibly damaged mitochondria. Mitophagy is majorly executed either by receptor-mediated or PINK1-Parkin-dependent pathways. Here, we show that the human orthologue of yeast Vms1, ANKZF1, participates in PINK-Parkin-mediated mitophagy. We show that ANKZF1 is extensively recruited to damaged mitochondria along with Parkin during mitochondrial proteotoxic stress induced by the expression of a single misfolded/aggregated protein or during uncoupler-induced membrane depolarization. Importantly, ANKZF1 recruitment to damaged mitochondria is significantly enhanced in the presence of Parkin, and ANKZF1 physically interacts with Parkin and LC3 during mitochondrial proteotoxic or depolarization stresses. ANKZF1 harbors six putative LC3-interacting regions (LIRs), LIR4 present at residues 333-336 is particularly important for ANKZF1-LC3 interaction. Furthermore, we show that ANKZF1 knockout cells are compromised in clearing stress-damaged mitochondria by mitophagy, indicating an important role of ANKZF1 in mitochondrial turnover during stress. In summary, we show a new role of ANKZF1 in eliminating the stress-damaged mitochondria, reiterating the mito-protective role of Vms1/ANKZF1 during mitochondrial stresses.

cell biology↗

Targeting an Olfactory Receptor Mitigates High Residual Platelet Reactivity and Arterial Thrombosis Through Actin Cytoskeleton Depolymerization

BackgroundDespite antiplatelet therapy, some patients remain at high risk for ischemic events due to medication non-responsiveness or High Residual Platelet Reactivity (HRPR). Our goal was to target an orphan G-Protein-Coupled Receptor (GPCR) on platelets belonging to the olfactory receptor family as a new antithrombotic strategy. MethodsUsing an engineered reporter cell line expressing Olfactory Receptor 2L13 (OR2L13) that was recently identified as an orphan GPCR to limit platelet reactivity, we performed a high-throughput screen (HST) of non-odorant bioactive compounds with counter-screen validation, followed by studies to determine changes in platelet function in healthy subjects and in patients with coronary artery disease and peripheral artery disease. Phospho-proteomics identified key signal transduction pathways, and a variety of ex vivo assays and in vivo functional studies examined the impact of an identified non-odorant compound on platelet signaling, platelet biomechanics, and thrombosis. ResultsWe identified 6 ligands specific for OR2L13 that function as receptor agonists, leading to the suppression of platelet aggregation and -granule exocytosis via P2Y12, PAR1, Thromboxane Receptor (TxR) and glycoprotein VI (GPVI) receptors, suggesting involvement of common downstream mediator. The lead OR2L13 agonist identified phosphorylates heat shock protein 27 (HSP27) and depolymerizes the platelet filamentous actin cytoskeleton which was further confirmed in a clot retraction assay (CCF0054500 clot area 70.6 vs. vehicle clot area 5.2, P<0.0001). This anti-thrombotic effect of the OR2L13 agonist was reversed by a HSP27 inhibitor (clot area 3.6, P<0.0001). In a murine cremaster arterial injury model, platelet accumulation at the injury site was reduced by 88.9% by the lead OR2L13 agonist compared to vehicle (P<0.0003) without altering fibrin generation in vivo, or interfering with the coagulation cascade, and without impairing the protective mechanism of platelet hemostasis. ConclusionWe describe and characterize the first non-olfactory tool to target an olfactory receptor for the purpose of inhibiting platelet activation and thrombosis through downstream HSP27 in a comprehensive investigation using a first-of-its kind platelet inhibitor targeting an orphan platelet GPCR.

physiology↗

Functional impact of the hyperduplication genomophenotype in high copy number endometrial cancer

High copy number endometrial cancers (HCNEC) are dominated by excessive duplications scattered across the genome, termed here as the HyperDuplication GenomoPhenotype (HDGP). Although correlated with cancer progression, its biological significance and implications for therapy have not yet been established. We identified locations and sizes of duplications in 171 endometrial cancer cases and designated 71 HCNEC cases as HDGP. We also investigated the response to the pan-ERBB inhibitor afatinib in a subset of HDGP-EC cases with ERBB2/ERBB3 duplications using a patient-derived three-dimensional culture model. Our analysis demonstrates that beyond tandem duplications there is a more general pattern involving coordinated duplication of multiple distant regions of the genome, demonstrating preferential selectivity to over-expressed potential oncogenes within a broad network. This suggests that HDGP increases tumor fitness and resistance to therapy by perturbing important gene networks in concert rather than only driver genes, suggesting a mechanistic basis for the ineffectiveness of targeted drugs in these patients and highlighting the need for combination therapies in these highly aggressive cases.

genomics↗

Directed disruption of IL2 aggregation sites produces designer biologics with enhanced specificity coupled to improved production capacity

The pleotropic nature of interleukin-2 (IL2) has allowed it to be used as both a pro-inflammatory and anti-inflammatory therapeutic agent, through promotion of regulatory T cell (Treg) responses via the IL2RA receptor or promotion of CD8 T cell responses via the IL2RB receptor, respectively. However, the utility of IL2 as a treatment is limited by this same pleiotropy, and protein engineering to bias specificity towards either the regulatory T cell (Treg) or CD8 T cell lineage often requires a trade-off in protein production or total bioactivity. Here we use SolubiS, a computational algorithm-based method, to predict mutations within the IL2 structure to improve protein production yield while altering cellular selectivity, to generate a mutein with elevated therapeutic potential. The design and testing process identified the V126R (murine) / V111R (human) mutation as a Treg-enhancing mutein, creating a cation repulsion to inhibit primary binding to IL2RB, with a post-IL2RA confirmational shift enabling secondary IL2RB binding, and hence allowing the trimeric receptor complex to form. In human IL2, additional N110R T151R aggregation-protecting mutations could improve protein yield of the V111R mutation. The approach also generated novel CD8 T cell-promoting mutations. Y79K created a cation-cation repulsion with IL2RA, while Q50W enhanced CD8 T cell activity through potential {pi}-stacking enhancing binding to IL2RB, with the combination highly stimulatory for CD8 T cells. For human IL2, Y65K (homolog to murine Y79K) coupled with E82K prevented IL2RA binding, however it required the aggregation-protecting mutations of N110R T151R to rescue production. These muteins, designed with both cellular specificity and protein production features, have potential as both biological tools and therapeutics.

immunology↗

Isolation, identification, and characterisation of the malachite green detoxifying bacterial strain Bacillus pacificus ROC1 and the azoreductase AzrC

Malachite green (MG) is used as a dye for materials such as wood, cotton, and nylon, and is used in aquaculture to prevent fungal and protozoan diseases. However, it is highly toxic, with carcinogenic, mutagenic, and teratogenic properties, resulting in bans worldwide. Despite this, MG is still frequently used in many countries due to its efficacy and economy. MG is persistent in the environment and so requires degradative intervention. In this work we isolated Bacillus pacificus ROC1 strain from a salt flat in Pakistan that had the ability to aerobically detoxify MG, as determined by bacterio- and phyto-toxicity assays. We demonstrate immobilized B. pacificus ROC1 can effectively detoxify MG, which highlights a potential method for its biodegradation. Genomic sequencing identified three candidate azo-reductases within B. pacificus ROC1 that could be responsible for the MG-degrading activity. These were cloned, expressed and purified from Escherichia coli, with one (AzrC), catalyzing the reduction of MG to leuco-MG in vitro. AzrC was crystallised and MG was captured within the active site in a Michaelis complex, providing structural insight into the reduction mechanism. Altogether, this work identifies a bacterium capable of aerobically degrading a major industrial pollutant and characterizes the molecular basis for this activity.

biochemistry↗

Leveraging Chlorination-Based Mechanism for Resolving Subcellular Hypochlorous Acid

Hypochlorous acid (HOCl) is crucial for pathogen defense, but an imbalance in HOCl levels can lead to tissue damage and inflammation. Existing HOCl indicators employ an oxidation approach, which may not truly reveal the chlorinative stress environment. We designed a suite of indicators with a new chlorination-based mechanism, termed HOClSense dyes, to resolve HOCl in sub-cellular compartments. HOClSense dyes allow the visualization of HOCl with both switch-on and switch-off detection modes with diverse emission colors, as well as a unique redshift in emission. HOClSense features a minimalistic design with impressive sensing performance in terms of HOCl selectivity, and our design also facilitates functionalization through click chemistry for resolving subcellular HOCl. As a proof of concept, we targeted plasma membrane and lysosomes with HOClSense for subcellular HOCl mapping. With utilizing HOClSense, we discovered the STING pathway-induced HOCl production and the abnormal HOCl production in Niemann-Pick diseases. To the best of our knowledge, this is the first chlorination-based HOCl indicator series for resolving subcellular HOCl.

cell biology↗

Deep Learning and 3D Imaging Reveal Whole-Body Alterations in Obesity

Many diseases, such as obesity, have systemic effects that impact multiple organ systems throughout the body. However, tools for comprehensive, high-resolution analysis of disease-associated changes at the whole-body scale have been lacking. Here, we developed a suite of deep learning-based image analysis algorithms (MouseMapper) and integrated it with tissue clearing and light-sheet microscopy to enable a comprehensive analysis of diseases impacting diverse systems across the mouse body. This approach enables the quantitative analysis of cellular and structural changes across the entire mouse body at unprecedented resolution and scale, including tracking nerves over several centimeters in whole animal bodies. To demonstrate its power, we applied MouseMapper to study nervous and immune systems in high-fat diet induced obesity. We uncovered widespread changes in both immune cell distribution and nerve structures, including alterations in the trigeminal nerve characterized by a reduced number of nerve endings in obese mice. These structural abnormalities were associated with functional deficits of whisker sensing and proteomic changes in the trigeminal ganglion, primarily affecting pathways related to axon growth and the complement system. Additionally, we found heterogeneity in obesity-induced whole-body inflammation across different tissues and organs. Our study demonstrates MouseMappers capability to discover and quantify pathological alterations at the whole-body level, offering a powerful approach for investigating the systemic impacts of various diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/608300v1_ufig1.gif" ALT="Figure 1"> View larger version (74K): org.highwire.dtl.DTLVardef@17d2601org.highwire.dtl.DTLVardef@14a2d3dorg.highwire.dtl.DTLVardef@e04114org.highwire.dtl.DTLVardef@d0b8b5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe developed MouseMapper: AI-driven pipeline for whole-body structural analysis in mice C_LIO_LIMouseMapper revealed obesity-induced changes in nerves and immune cells across multiple organs C_LIO_LIMouseMapper identified facial nerve alterations in obesity linked to impaired whisker sensitivity C_LIO_LIMouseMapper has the potential for holistic 3D analysis of systemic diseases C_LI Supplementary Videos can be seen at: http://discotechnologies.org/MouseMapper/

systems biology↗

iSODA: A Comprehensive Tool for Integrative Omics Data Analysis in Single- and Multi-Omics Experiments

Omics technologies including genomics, proteomics, metabolomics, and lipidomics allow profound insights into health and disease. Thanks to plummeting costs of continuously evolving omics analytical platforms, research centers collect multi-omics data more routinely. They are, however, confronted with the lack of a versatile software solution to harmoniously analyze single-omics data and merge and interpret multi-omics data. We have developed iSODA, an interactive web-based application for the analysis of single-as well as multi-omics omics data. The software tool emphasizes intuitive, interactive visualizations designed for user-driven data exploration. Researchers can filter and normalize their datasets and access a variety of functions ranging from simple data visualization like volcano plots and PCA, to advanced functional analyses like enrichment analysis for proteomics and saturation analysis for lipidomics. For insights from integrated multi-omics, iSODA incorporates Multi-Omics Factor Analysis - MOFA, and Similarity Network Fusion - SNF. All results are presented in interactive plots with the possibility of downloading plots and associated data. The ability to adapt the imported data on-the-fly allows for tasks such as removal of outlier samples or failed features, various imputation strategies, or data normalization. The modular design allows for extensions with new analyses and plots. The software is accessible under http://isoda.online/. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/605811v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1eb61c8org.highwire.dtl.DTLVardef@60a7feorg.highwire.dtl.DTLVardef@1b54b41org.highwire.dtl.DTLVardef@15fd1b2_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical summary for iSODA showcasing some application examples, the data import, the single-omics and multi-omics modules.

bioinformatics↗

Synapse protein signatures in cerebrospinal fluid and plasma predict cognitive maintenance versus decline in Alzheimers disease

Rates of cognitive decline in Alzheimers disease (AD) are extremely heterogeneous, with ages of symptom onset ranging from age 40-100 years and conversion from mild cognitive impairment to AD dementia taking 2-20 years. Development of biomarkers for amyloid-beta (A{beta}) and tau protein aggregates, the hallmark pathologies of AD, have improved patient monitoring/stratification and drug development, but they still only explain 20-40% of the variance in cognitive impairment (CI) in AD. To discover additional molecular drivers and biomarkers of AD dementia, we perform cerebrospinal fluid (CSF) proteomics on 3,416 individuals from six deeply phenotyped prospective AD case-control cohorts. We identify synapse proteins as the strongest correlates of CI, independent of A{beta} and tau. Using machine learning we derive the CSF YWHAG:NPTX2 synapse protein ratio, a robust correlate of CI, which explains 27% of the variance in CI beyond CSF PTau181:A{beta}42, 10% beyond tau PET, and 50% beyond CSF NfL in A{beta} positive individuals. We find YWHAG:NPTX2 also increases with normal aging as early as age 20 and increases at a faster rate in APOE4 carriers and autosomal dominant-AD mutation carriers. Most notably, YWHAG:NPTX2+ individuals (top 25th percentile) are 15-times (HR=15.4 [10.6-22.2]) more likely to experience cognitive decline over 15 years compared to YWHAG:NPTX2- individuals (bottom 25th percentile), and this rises to 19-times (HR=18.9 [10.83-32.9]) with additional stratification by A{beta} and phosphorylated tau status. Lastly, we perform plasma proteomics on 4,245 individuals to develop a plasma-based signature of CI which partly recapitulates CSF YWHAG:NPTX2. Overall, our findings underscore CSF YWHAG:NPTX2 and the corresponding plasma signature as robust prognostic biomarkers for AD onset and progression beyond gold-standard biomarkers of A{beta}, tau, and neurodegeneration and implicate synapse dysfunction as a core driver of AD dementia.

neuroscience↗

Elevated body mass index in youth is associated with dysregulated surrogate markers of neural inhibition & excitation, and internetwork functional dysconnectivity

The developing child and adolescent brain is thought to have an increased vulnerability to the negative impact of obesity and excessive consumption of hyperpalatable and energy-rich foods. In this study, we investigated the neurophysiological effects of overweight and obesity in 30 participants spanning childhood and adolescence (8-19 years), using a naturalistic viewing paradigm with Inscapes, in a pseudo-resting-state protocol scan with magnetoencephalography (MEG). Subjects were median split on body mass indices (BMI), categorised into two groups comprising: lower <25 kg/m2 (n=15) and higher [&ge;]25 kg/m2 (n=15). We assessed spontaneous, regional neural function indexed by oscillatory activity, and functional connectivity within and between intrinsic resting brain networks, including the default mode network, dorsal and ventral attention, somatomotor, visual, language, central executive and salience networks. Elevated BMI was associated with significant reductions in activity of the posterior dominant rhythm, and gamma hyperactivity across widespread cortical areas, suggesting intrinsic neuronal hyperexcitability and disinhibition in children and adolescents. Additionally, we observed low-frequency theta hypoconnectivity between resting state networks including the salience, visual, and default mode networks, and overall reduced global efficiency in brain network structure, suggesting reduced effectiveness in neural communication. These findings underscore the neural impact of body composition on the developing brain, suggesting deleterious alterations in excitation and inhibition from surrogate neural markers associated with neurochemistry and brain networks linked with cognitive and behavioural functioning. These alterations may contribute to the persistent behavioural rigidity and difficulties in adopting healthier eating behaviours into adulthood.

neuroscience↗

Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion

Purposeaccurate modeling of blood dynamics in the coronary microcirculation is a crucial step towards the clinical application of in silico methods for the diagnosis of coronary artery disease (CAD). In this work, we present a new mathematical model of microcirculatory hemodynamics accounting for microvasculature compliance and cardiac contraction; we also present its application to a full simulation of hyperemic coronary blood flow and 3D myocardial perfusion in real clinical cases. Methodsmicrovasculature hemodynamics is modeled with a compliant multi-compartment Darcy formulation, with the new compliance terms depending on the local intramyocardial pressure generated by cardiac contraction. Nonlinear analytical relationships for vessels distensibility are included based on experimental data, and all the parameters of the model are reformulated based on histologically relevant quantities, allowing a deeper model personalization. ResultsPhasic flow patterns of high arterial inflow in diastole and venous outflow in systole are obtained, with flow waveforms morphology and pressure distribution along the microcirculation reproduced in accordance with experimental and in vivo measures. Phasic diameter change for arterioles and capillaries is also obtained with relevant differences depending on the depth location. Coronary blood dynamics exhibits a disturbed flow at the systolic onset, while the obtained 3D perfusion maps reproduce the systolic impediment effect and show relevant regional and transmural heterogeneities in myocardial blood flow (MBF). Conclusionthe proposed model successfully reproduces microvasculature hemodynamics over the whole heartbeat and along the entire intramural vessels. Quantification of phasic flow patterns, diameter changes, regional and transmural heterogeneities in MBF represent key steps ahead in the direction of the predictive simulation of cardiac perfusion.

bioengineering↗

GraphCompass: Spatial metrics for differential analyses of cell organization across conditions

Spatial omics technologies are increasingly leveraged to characterize how disease disrupts tissue organization and cellular niches. While multiple methods to analyze spatial variation within a sample have been published, statistical and computational approaches to compare cell spatial organization across samples or conditions are mostly lacking. We present GraphCompass, a comprehensive set of omics-adapted graph analysis methods to quantitatively evaluate and compare the spatial arrangement of cells in samples representing diverse biological conditions. GraphCompass builds upon the Squidpy spatial omics toolbox and encompasses various statistical approaches to perform cross-condition analyses at the level of individual cell types, niches, and samples. Additionally, GraphCompass provides custom visualization functions that enable effective communication of results. We demonstrate how GraphCompass can be used to address key biological questions, such as how cellular organization and tissue architecture differ across various disease states and which spatial patterns correlate with a given pathological condition. GraphCompass can be applied to various popular omics techniques, including, but not limited to, spatial proteomics (e.g. MIBI-TOF), spot-based transcriptomics (e.g. 10x Genomics Visium), and single-cell resolved transcriptomics (e.g. Stereo-seq). In this work, we showcase the capabilities of GraphCompass through its application to three different studies that may also serve as benchmark datasets for further method development. With its easy-to-use implementation, extensive documentation, and comprehensive tutorials, GraphCompass is accessible to biologists with varying levels of computational expertise. By facilitating comparative analyses of cell spatial organization, GraphCompass promises to be a valuable asset in advancing our understanding of tissue function in health and disease.

bioinformatics↗

Systematic characterization of protein structural features of alternative splicing isoforms using AlphaFold 2

Alternative splicing is an important cellular process in eukaryotes, altering pre-mRNA to yield multiple protein isoforms from a single gene. However, our understanding of the impact of alternative splicing events on protein structures is currently constrained by a lack of sufficient protein structural data. To address this limitation, we employed AlphaFold 2, a cutting-edge protein structure prediction tool, to conduct a comprehensive analysis of alternative splicing for approximately 3,000 human genes, providing valuable insights into its impact on the protein structural. Our investigation employed state of the art high-performance computing infrastructure to systematically characterize structural features in alternatively spliced regions and identified changes in protein structure following alternative splicing events. Notably, we found that alternative splicing tends to alter the structure of residues primarily located in coils and beta-sheets. Our research highlighted a significant enrichment of loops and highly exposed residues within human alternatively spliced regions. Specifically, our examination of the Septin-9 protein revealed potential associations between loops and alternative splicing, providing insights into its evolutionary role. Furthermore, our analysis uncovered two missense mutations in the Tau protein that could influence alternative splicing, potentially contributing to the pathogenesis of Alzheimers disease. In summary, our work, through a thorough statistical analysis of extensive protein structural data, sheds new light on the intricate relationship between alternative splicing, evolution, and human disease.

bioinformatics↗

Enhancer Binding Proteins Regulate Natural Product Biosynthesis in Photorhabdus laumondii

Biosynthetic gene clusters are readily transferred between microbes through horizontal gene transfer, but to provide benefit to their host they must be induced to high levels during times of stress. Working with the insect pathogen Photorhabdus laumondii, here we study the effect of plasmid-induced stress on natural product biosynthesis. We find that the expression plasmid pARO190 alone was sufficient to induce production of an array of natural products, and that the induction could be increased with heterologous expression of either bacterial enhancer binding proteins or a random DNA sequence. Overall, this suggests that generalized stress may be an effective way to increase production of natural products in P. laumondii.

microbiology↗

The mitochondrial mRNA stabilizing protein, SLIRP, regulates skeletal muscle mitochondrial structure and respiration by exercise-recoverable mechanisms

Summary and graphical abstractDecline in mitochondrial function associates with decreased muscle mass and strength in multiple conditions, including sarcopenia and type 2 diabetes. Optimal treatment could include improving mitochondrial function, however, there are limited and equivocal data regarding the molecular cues controlling muscle mitochondrial plasticity. Here we uncover the mitochondrial-mRNA-stabilizing protein SLIRP, in complex with LRPPRC, as a PGC-1 target that regulates mitochondrial structure, respiration, and mitochondrially-encoded-mRNA pools in skeletal muscle. Exercise training effectively counteracted mitochondrial defects induced by loss of LRPPRC/SLIRP, despite sustained low mitochondrially-encoded-mRNA pools, via increased mitoribosome translation capacity. In humans, exercise training robustly increased muscle SLIRP and LRPPRC protein content across exercise modalities and sexes, yet this increase was less prominent in subjects with type 2 diabetes. Our work identifies a mechanism of post-transcriptional mitochondrial regulation in skeletal muscle through mitochondrial mRNA stabilization. It emphasizes exercise as an effective approach to alleviate mitochondrial defects by possibly increasing mitoribosome capacity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/564600v2_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@1cdc6c5org.highwire.dtl.DTLVardef@b4cb1borg.highwire.dtl.DTLVardef@182871corg.highwire.dtl.DTLVardef@7462ea_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗