Biology subjects

Kim, M.

Publications and source records attributed to Kim, M..

At least 199 records · Page 11Linked to original sources

bioRxiv2024

High-Resolution Spatial Transcriptomic Atlas of Mouse Soleus Muscle: Unveiling Single Cell and Subcellular Heterogeneity in Health and Denervation

Skeletal muscle exhibits pronounced cellular and subcellular heterogeneity, but comprehensive spatial mapping has been constrained by cell/nuclei dissociation-based methods that lose tissue architecture and by spatial platforms with insufficient resolution or limited transcriptome coverage. Here we present a high-resolution spatial transcriptomic atlas of mouse soleus muscle in longitudinal sections with unbiased whole-transcriptome coverage, enabling myofiber-resolved transcriptomes while preserving subcellular expression domains across the length of fibers. Combining histology-guided myofiber segmentation with unbiased grid-based mapping, we recover canonical fiber types and reveal widespread hybrid myofiber states in situ, including type IIb-associated signatures that are rare in soleus muscle and evident only when intramyofiber heterogeneity is assessed. At subcellular scale, we delineate the neuromuscular junction (NMJ) as a multi-compartment niche comprising postsynaptic myonuclei and spatially distinct peri-synaptic and myelinating Schwann cell-associated regions, each with characteristic gene programs. Applying this framework to denervation (3 and 7 days) identifies robust fiber-type-specific stress responses, coordinated remodeling of macrophage and fibroblast transcriptomes, and marked intramyofiber heterogeneity, including spatially nonuniform activation of damage-response genes along individual myofibers, with distinct transcriptional domains proximal and distal to the NMJ and associated degenerative histological features. Together, this atlas provides a high-resolution reference for muscle biology and clarifies how denervation reshapes myofiber, synaptic, and stromal-immune programs across cells and within cells in intact tissue.

physiology↗

bioRxiv2024

In-situ microscopy-assisted meniscus-guided coating for highly sensitive reduced graphene oxide-based nanocomposite biosensor

Meniscus-guided coating provides great potential for fabricating the nanomaterial-based thin film into high-performance biomedical devices due to the strong relationship between its experimental parameters and the resulting structural properties. However, the complex leverages of various fluid dynamics phenomena hamper optimization of structural properties and device performances. This is due to the absence of in-depth analytical techniques to observe, interpret, and control the solidification process. In this work, we propose an analytical strategy based on the rheological properties of a rGO-based solution using computational fluid dynamics modeling and in situ high-speed microscopy. Through this, we reveal the principles of the solidification mechanism that creates a rGO-based nanocomposite in the form of highly- and evenly-wrinkled thin film and the experimental condition at which this mechanism occurs. The optimized thin film presents high electroconductivity, low chip-to-chip signal variation, and multiplexed electrochemical biosensing performance for three classes of antibodies related to the excessive enrichment of endoplasmic reticulum stress, with detection limits of picomolar levels. This optimizing technique can be universally applied to understanding various solution-based coating systems, and can streamline the production of large-area and high-quality nanocomposite biosensors.

bioengineering↗

bioRxiv2024

Personalized composite scaffolds for accelerated cell- and growth factor-free craniofacial bone regeneration

Approaches to regenerating bone often rely on the integration of biomaterials and biological signals in the form of cells or cytokines. However, from a translational point of view, these approaches face challenges due to the sourcing and quality of the biologic, unpredictable immune responses, complex regulatory paths, and high costs. We describe a simple manufacturing process and a material-centric 3D-printed composite scaffold system (CSS) that offers distinct advantages for clinical translation. The CSS comprises a 3D-printed porous polydiolcitrate-hydroxyapatite composite elastomer infused with a polydiolcitrate-graphene oxide hydrogel composite. Using a continuous liquid interface production 3D printer, we fabricate a precise porous ceramic scaffold with 60% hydroxyapatite content resembling natural bone. The resulting scaffold integrates with a thermoresponsive hydrogel composite, customizable in situ to fit the defect. This hybrid phasic porous CSS mimics the bone microenvironment (inorganic and organic) while allowing independent control of each material phase (rigid and soft). The CSS stimulates osteogenic differentiation in vitro and in vivo. Moreover, it promotes M2 polarization and blood vessel ingrowth, which are crucial for supporting bone formation. Our comprehensive micro-CT analysis revealed that within 4 weeks in a critical-size defect model, the CSS accelerated ECM deposition (8-fold) and mineralized osteoid (69-fold) compared to the untreated. Our material-centric approach delivers impressive osteogenic properties and streamlined manufacturing advantages, potentially expediting clinical application for bone reconstruction surgeries.

bioengineering↗

bioRxiv2024

Circadian rhythms of macrophages are altered by the acidic pH of the tumor microenvironment

Macrophages are prime therapeutic targets due to their pro-tumorigenic and immunosuppressive functions in tumors, but the varying efficacy of therapeutic approaches targeting macrophages highlights our incomplete understanding of how the tumor microenvironment (TME) can influence regulation of macrophages. The circadian clock is a key internal regulator of macrophage function, but how circadian rhythms of macrophages may be influenced by the tumor microenvironment remains unknown. We found that conditions associated with the TME such as polarizing stimuli, acidic pH, and elevated lactate concentrations can each alter circadian rhythms in macrophages. Circadian rhythms were enhanced in pro-resolution macrophages but suppressed in pro-inflammatory macrophages, and acidic pH had divergent effects on circadian rhythms depending on macrophage phenotype. While cyclic AMP (cAMP) has been reported to play a role in macrophage response to acidic pH, our results indicate that pH-driven changes in circadian rhythms are not mediated solely by the cAMP signaling pathway. Remarkably, clock correlation distance analysis of tumor-associated macrophages (TAMs) revealed evidence of circadian disorder in TAMs. This is the first report providing evidence that circadian rhythms of macrophages are altered within the TME. Our data further suggest that heterogeneity in circadian rhythms at the population level may underlie this circadian disorder. Finally, we sought to determine how circadian regulation of macrophages impacts tumorigenesis, and found that tumor growth was suppressed when macrophages had a functional circadian clock. Our work demonstrates a novel mechanism by which the tumor microenvironment can influence macrophage biology through altering circadian rhythms, and the contribution of circadian rhythms in macrophages to suppressing tumor growth.

immunology↗

bioRxiv2024

DYRKP kinase regulates cell wall degradation in Chlamydomonas by inducing matrix metalloproteinase expression

The cell wall of plants and algae is an important cell structure that protects cells from changes in the external physical and chemical environment. This extracellular matrix composed of polysaccharides and glycoproteins, is needed to be remodeled continuously throughout the life cycle. However, compared to matrix polysaccharides, little is known about the mechanisms regulating the formation and degradation of matrix glycoproteins. We report here that a plant kinase belonging to the dual-specificity tyrosine phosphorylation-regulated kinase (DYRK) family present in all eukaryotes regulates cell wall degradation in the model microalga Chlamydomonas reinhardtii by inducing the expression of matrix metalloproteinases (MMPs). In the absence of DYRKP, daughter cells fail to degrade the parental cell wall, and form multicellular structures. On the other hand, the complementation line of DYRKP was shown to degrade the parental cell wall normally. Transcriptomic and proteomic analyses indicate a marked down-regulation of MMP expression in the dyrkp mutants. Additionally, the expression of MMP was confirmed to be consistent with the expression pattern of DYRKP. Our findings show that DYRKP, by ensuring timely MMP expression, enables the successful execution of the cell cycle. Altogether, this study provides new insight into the life cycle regulation in plants and algae. IN A NUTSHELLO_ST_ABSBackgroundC_ST_ABSPlants and algae have different types of polysaccharides in their cell walls, but they have glycoproteins in common. Glycoprotein synthesis and degradation must be tightly regulated to ensure normal growth and differentiation. However, little is known about the regulatory mechanism of glycoprotein degradation in both plants and algae. The cell cycle of Chlamydomonas reinhardtii begins anew with the hatching of daughter cells, and the role of matrix metalloproteinases (MMPs) is known to be important in this process. In our previous study, we observed that a knockout mutant of the plant kinase belonging to the dual-specificity tyrosine phosphorylation-regulated kinase (DYRKP) formed a palmelloid structure and failed to hatch. QuestionsWhat is the role of DYRKP in microalgae? Specifically, why does the dyrkp mutant form a palmelloid structure? Palmelloid is usually observed in dividing cells or after exposure to stresses. We therefore hypothesized that the palmelloid phenotype observed in dyrkp mutant could either be due to a defect in cell hatching or due to an increased stress state in the mutant population. FindingsWe answered these questions by comparative studies in different culture conditions and by examining additional dyrkp knockout mutants generated by CRISPR-Cas9 in various background strains with more or less intact cell walls. Palmelloid formation in the dyrkp mutant was observed under optimal growth (mixo- or auto-trophic condition) and very low light conditions. Interestingly, unlike the parent strain, in which only cell wall fragments are observed in old cultures, the parental cell wall of the dyrkp mutant remained almost intact even after the release of daughter cells. Also, the cell division rate of the cell wall-less dyrkp mutants was similar to their background strain. These results suggest that dyrkp mutants have a problem in degrading the parental cell walls. Indeed, proteomic and transcriptomic analyses revealed reduced levels of protease families in the dyrkp mutant, and in particular with a significantly lower amount of several key members of the MMP family. Through the analysis of complementation lines, we confirmed that the DYRKP was required for strong and rapid expression of MMPs. Next stepsWe are pursuing research to understand what the phosphorylation clients of DYRKP are and how they regulate the expression of the MMPs identified in this study. One sentence summaryThe DYRKP kinase induces the expression of matrix metalloproteinases involved in the degradation of the parental cell wall, allowing prompt hatching of daughter cells after cell division.

plant biology↗

bioRxiv2024

Phototropin connects blue light perception to starch metabolism in green algae

In photosynthetic organisms light acts as an environmental signal to control their development and physiology, and as energy source to drive the conversion of CO2 into carbohydrates used for growth or storage. The main storage carbohydrate in green algae is starch, which accumulates during the day and is broken down at night to meet cellular energy demands. The signalling role of light quality in the regulation of starch accumulation remains unexplored. Here, we identify PHOTOTROPIN-MEDIATED SIGNALLING KINASE 1 (PMSK1) as a key regulator of starch metabolism in Chlamydomonas reinhardtii. In its phosphorylated form (PMSK1-P), it activates GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE (GAP1), promoting starch biosynthesis. We show that blue light, perceived by PHOTOTROPIN, induces PMSK1 dephosphorylation that in turn represses GAP1 mRNA levels and reduces starch accumulation. These findings reveal a novel blue light-mediated signaling pathway that advances our understanding of photoreceptor-controlled carbon metabolism in microalgae. One-Sentence SummaryBlue light perception by PHOTOTROPIN triggers kinase-mediated signaling to inhibit starch accumulation in the green alga Chlamydomonas.

plant biology↗

bioRxiv2024

Determining susceptibility loci in triple negative breast cancer using a novel pre-clinical model

Breast cancer (BC) is the most common cancer and the second cause of death in US women. Our lack of understanding of how genetic variants affect molecular mechanisms that mediate BC aggression poses a substantial obstacle to advancements in cancer diagnosis and therapy. To examine genetic variants on BC traits, a novel murine model was created with robust phenotypic and genomic variation. The FVB C3(1)-T-antigen ("C3Tag") mouse develops spontaneous tumors in the mammary glands of female mice with a mean latency of 4-5 months of age. This genetically engineered mouse model (GEMM) is well established to resemble human basal-like TNBC. TNBC is an aggressive subtype with few clinical approaches and poor patient outcomes. Thus, to model human heterogeneity in BC outcomes, we systematically crossed the C3Tag GEMM into the BXD recombinant inbred family - the largest and best characterized genetic reference population. The new model is termed "BXD-BC" and F1 hybrids of the cross have isogenic genomes that are reproducible. BXD-BCs are a potent tool to determine the impact of genetic modifiers on BC tumor traits. We hypothesized that examination of BXD-BC GEMMs will enable the identification of susceptibility loci, candidate genes, and molecular networks that underlie variation of multiple BC phenotypes. Using N=29 BXD-BC strains, we demonstrated significant heritable variations in the severity of TNBC characteristics such as tumor latency, multiplicity, and survival. Interestingly, 2 BXD-BC strains never developed tumors out to 1 year of age. Thus, BXD-BC strains demonstrate variance in cancer susceptibility and progression compared to the parent C3Tag GEMM, indicating the presence of genetic modifiers. Through an unbiased systematic quantification of breast cancer severity across BXD-BC hybrids, we identified several significant quantitative trait loci (QTL) and candidate genes for specific tumor traits. In combination with public human GWAS datasets, we defined syntenic regions, candidate genes, and underlying networks through cross-species systems genetics analyses to demonstrate the translational validity of conserved, biologically relevant, and targetable candidates. Our findings suggest conserved candidates predicting TNBC patient survival. In sum, the BXD-BC resource is an innovative, reliable, and robust preclinical model that reflects robust genetic heterogeneity. Using cutting edge systems genetics, we have identified genetic modifiers of BC phenotypic variation that could be targeted to advance therapeutic limitations or as biomarkers of risk or response to therapy.

genetics↗

bioRxiv2024

Inositol polyphosphate multikinase regulates Th1 and Th17 cell differentiation by controlling Akt-mTOR signaling

Activated proinflammatory T helper (Th) cells, such as Th1 and Th17 cells, mediate immune responses against intra- and extra-cellular pathogens as well as cause the development of various autoimmune diseases. Inositol polyphosphate multikinase (IPMK) is a key enzyme essential for inositol phosphate and phosphoinositide metabolism, which is known to control major biological events such as growth; however, its role in the function of Th cells remains unclear. Here we show that the expression of IPMK is highly induced in distinct Th1 and Th17 subsets. Further, while conditional deletion of IPMK in CD4+ T cells is dispensable for Th2-dependent immune responses, both Th1- and Th17-mediated immune responses are markedly diminished when this enzyme is absent resulting in reduced resistance to Leishmania major infection and attenuation of experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. In addition, IPMK-deficient naive CD4+ T cells display aberrant T cell activation and impaired differentiation into Th17 cells, which is associated with reduced activation of Akt, mechanistic target of rapamycin (mTOR), and STAT3. Mechanistically, IPMK as a phosphatidylinositol 3-kinase (PI3-kinase) controls the production of phosphatidylinositol (3,4,5)-trisphosphate, thereby promoting T cell activation, differentiation, and effector functions. Our findings suggest that IPMK acts as a critical regulator of Th1 and Th17 differentiation, highlighting the physiological importance of IPMK in Th1- and Th17-mediated immune homeostasis.

immunology↗

bioRxiv2023

Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin Interactions

Dictionary learning (DL), implemented via matrix factorization (MF), is commonly used in computational biology to tackle ubiquitous clustering problems. The method is favored due to its conceptual simplicity and relatively low computational complexity. However, DL algorithms produce results that lack interpretability in terms of real biological data. Additionally, they are not optimized for graph-structured data and hence often fail to handle them in a scalable manner. In order to address these limitations, we propose a novel DL algorithm called online convex network dictionary learning (online cvxNDL). Unlike classical DL algorithms, online cvxNDL is implemented via MF and designed to handle extremely large datasets by virtue of its online nature. Importantly, it enables the interpretation of dictionary elements, which serve as cluster representatives, through convex combinations of real measurements. Moreover, the algorithm can be applied to data with a network structure by incorporating specialized subnetwork sampling techniques. To demonstrate the utility of our approach, we apply cvxNDL on 3D-genome RNAPII ChIA-Drop data with the goal of identifying important long-range interaction patterns (long-range dictionary elements). ChIA-Drop probes higher-order interactions, and produces data in the form of hypergraphs whose nodes represent genomic fragments. The hyperedges represent observed physical contacts. Our hypergraph model analysis has the objective of creating an interpretable dictionary of long-range interaction patterns that accurately represent global chromatin physical contact maps. Through the use of dictionary information, one can also associate the contact maps with RNA transcripts and infer cellular functions. To accomplish the task at hand, we focus on RNAPII-enriched ChIA-Drop data from Drosophila Melanogaster S2 cell lines. Our results offer two key insights. First, we demonstrate that online cvxNDL retains the accuracy of classical DL (MF) methods while simultaneously ensuring unique interpretability and scalability. Second, we identify distinct collections of proximal and distal interaction patterns involving chromatin elements shared by related processes across different chromosomes, as well as patterns unique to specific chromosomes. To associate the dictionary elements with biological properties of the corresponding chromatin regions, we employ Gene Ontology (GO) enrichment analysis and perform multiple RNA coexpression studies. Availability and ImplementationThe code and test datasets are available at:\ https://github.com/rana95vishal/chromatin_DL/ Author summaryWe introduce a novel method for dictionary learning termed online convex Network Dictionary Learning (online cvxNDL). The method operates in an online manner and utilizes representative subnetworks of a network dataset as dictionary elements. A key feature of online cvxNDL is its ability to work with graph-structured data and generate dictionary elements that represent convex combinations of real data points, thus ensuring interpretability. Online cvxNDL is used to investigate long-range chromatin interactions in S2 cell lines of Drosophila Melanogaster obtained through RNAPII ChIA-Drop measurements represented as hypergraphs. The results show that dictionary elements can accurately and efficiently reconstruct the original interactions present in the data, even when subjected to convexity constraints. To shed light on the biological relevance of the identified dictionaries, we perform Gene Ontology enrichment and RNA-seq coexpression analyses. These studies uncover multiple long-range interaction patterns that are chromosome-specific. Furthermore, the findings affirm the significance of convex dictionaries in representing TADs cross-validated by imaging methods (such as 3-color FISH (fluorescence in situ hybridization)).

genomics↗

bioRxiv2023

Identification and Analysis of SARS-CoV-2 Mutation and Subtype using 2x tiled Primer Set with Oxford Nanopore Technologies Sequencing for Enhanced Variant Detection and Surveillance in Seoul, Korea

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a respiratory virus that contains RNA as its genetic material and has caused a global pandemic since its outbreak in 2020. This virus has many mutations, some of which can reduce the effectiveness of existing vaccines. Therefore, next-generation sequencing (NGS) is necessary to accurately identify new mutations. Current NGS analysis of SARS-CoV-2 uses the amplicon analysis method through a multiplex polymerase chain reaction. This study collected and validated RNA samples from patients who tested positive for SARS-CoV-2 from April to July 2022, and selected 613 samples for sequencing. The findings demonstrate the importance of long-read-based NGS analysis and 2x tiled primer set for identifying full SARS-CoV-2 genome sequence with new mutations and understanding the correlation between viral genotypes and patient characteristics for the effective management of SARS-CoV-2.

microbiology↗

bioRxiv2023

Mapping Cerebellar Anatomical Heterogeneity in Mental and Neurological Illnesses

The cerebellum has been linked to motor coordination, cognitive and affective processing, in addition to a wide range of clinical illnesses. To enable robust quantification of individual cerebellar anatomy relative to population norms, we mapped the normative development and aging of the cerebellum across the lifespan using brain scans of > 54k participants. We estimated normative models at voxel-wise spatial precision, enabling integration with cerebellar atlases. Applying the normative models in independent samples revealed substantial heterogeneity within five clinical illnesses: autism spectrum disorder, mild cognitive impairment, Alzheimers disease, bipolar disorder, and schizophrenia. Notably, individuals with autism spectrum disorder and mild cognitive impairment exhibited increased numbers of both positive and negative extreme deviations in cerebellar anatomy, while schizophrenia and Alzheimers disease predominantly showed negative deviations. Finally, extreme deviations were associated with cognitive scores. Our results provide a voxel-wise mapping of cerebellar anatomy across the human lifespan and clinical illnesses, demonstrating cerebellums nuanced role in shaping human neurodiversity across the lifespan and in different clinical illnesses.

neuroscience↗

bioRxiv2023

Neuroinflammation in post-acute sequelae of COVID-19 (PASC) as assessed by PBR28 PET correlates with vascular disease measures

The COVID-19 pandemic caused by SARS-CoV-2 has triggered a consequential public health crisis of post-acute sequelae of COVID-19 (PASC), sometimes referred to as long COVID. The mechanisms of the heterogeneous persistent symptoms and signs that comprise PASC are under investigation, and several studies have pointed to the central nervous and vascular systems as being potential sites of dysfunction. In the current study, we recruited individuals with PASC with diverse symptoms, and examined the relationship between neuroinflammation and circulating markers of vascular dysfunction. We used [11C]PBR28 PET neuroimaging, a marker of neuroinflammation, to compare 12 PASC individuals versus 43 normative healthy controls. We found significantly increased neuroinflammation in PASC versus controls across a wide swath of brain regions including midcingulate and anterior cingulate cortex, corpus callosum, thalamus, basal ganglia, and at the boundaries of ventricles. We also collected and analyzed peripheral blood plasma from the PASC individuals and found significant positive correlations between neuroinflammation and several circulating analytes related to vascular dysfunction. These results suggest that an interaction between neuroinflammation and vascular health may contribute to common symptoms of PASC.

neuroscience↗

bioRxiv2023

Pan-cancer analysis reveals multifaceted roles of retrotransposon-fusion RNAs

Transposon-derived transcripts are abundant in RNA sequences, yet their landscape and function, especially for fusion transcripts derived from unannotated or somatically acquired transposons, remains underexplored. Here, we developed a new bioinformatic tool to detect transposon-fusion transcripts in RNA-sequencing data and performed a pan-cancer analysis of 10,257 cancer samples across 34 cancer types as well as 3,088 normal tissue samples. We identified 52,277 cancer-specific fusions with [~]30 events per cancer and hotspot loci within transposons vulnerable to fusion formation. Exonization of intronic transposons was the most prevalent genic fusions, while somatic L1 insertions constituted a small fraction of cancer-specific fusions. Source L1s and HERVs, but not Alus showed decreased DNA methylation in cancer upon fusion formation. Overall cancer-specific L1 fusions were enriched in tumor suppressors while Alu fusions were enriched in oncogenes, including recurrent Alu fusions in EZH2 predictive of patient survival. We also demonstrated that transposon-derived peptides triggered CD8+ T-cell activation to the extent comparable to EBV viruses. Our findings reveal distinct epigenetic and tumorigenic mechanisms underlying transposon fusions across different families and highlight transposons as novel therapeutic targets and the source of potent neoantigens.

cancer biology↗

bioRxiv2023

Synchronized long-read genome, methylome, epigenome, and transcriptome for resolving a Mendelian condition

Resolving the molecular basis of a Mendelian condition (MC) remains challenging owing to the diverse mechanisms by which genetic variants cause disease. To address this, we developed a synchronized long-read genome, methylome, epigenome, and transcriptome sequencing approach, which enables accurate single-nucleotide, insertion-deletion, and structural variant calling and diploid de novo genome assembly, and permits the simultaneous elucidation of haplotype-resolved CpG methylation, chromatin accessibility, and full-length transcript information in a single long-read sequencing run. Application of this approach to an Undiagnosed Diseases Network (UDN) participant with a chromosome X;13 balanced translocation of uncertain significance revealed that this translocation disrupted the functioning of four separate genes (NBEA, PDK3, MAB21L1, and RB1) previously associated with single-gene MCs. Notably, the function of each gene was disrupted via a distinct mechanism that required integration of the four omes to resolve. These included nonsense-mediated decay, fusion transcript formation, enhancer adoption, transcriptional readthrough silencing, and inappropriate X chromosome inactivation of autosomal genes. Overall, this highlights the utility of synchronized long-read multi-omic profiling for mechanistically resolving complex phenotypes.

genetics↗

bioRxiv2023

Slave Trade and Colonial Expansion Resulted in Strong Sex-Biased Admixture in South Africa

The colonial-period arrival of Europeans in southern Africa is associated with strong sex-biased migration by which male settlers displaced indigenous Khoekhoe and San men. Simultaneously, the importation of South Asian, Indonesian and Eastern African slaves may have contributed female-biased migration to Cape Town and surrounding areas. We examine the spatial and temporal spread of sex-biased migration from the Cape northward into Namaqualand and the southern Kalahari using genetic data from more than 1,400 individuals. In all regions, admixture patterns were sex-biased, with evidence of a greater male contribution of European ancestry and greater female contribution of Khoe-San ancestry. While admixture among Khoe-San, European, equatorial African, and Asian groups has likely been continuous from the founding of Cape Town to present-day, we find that Khoe-San groups further north experienced a single pulse of European admixture 6-8 generations ago. European admixture was followed by additional Khoe-San gene flow, potentially reflecting an aggregation of indigenous groups due to disruption by colonial interlopers. Male migration into the northern frontier territories was not a homogenous group of expanding Afrikaners and slaves. The Nama show evidence of distinct founder effects and derive 15% of their male lineages from Asian men, a pattern absent in the =Khomani San. Khoe-San ancestry from the paternal line is greatly diminished in populations from Cape Town, the Cederberg Mountains and Upington, but remains more frequent in self-identified ethnically indigenous groups. Strikingly, we estimate that Khoe-San Y-chromosomes were experiencing unprecedented population growth at the time of European arrival. Our findings shed light on the patterns of admixture and the population history of South Africa as the colonial frontier expanded.

genetics↗

bioRxiv2023

GraphMHC: neoantigen prediction model applying the graph neural network to molecular structure

Neoantigens are biomarkers that can predict the prognosis associated with immune checkpoint inhibition by estimating the binding potential of candidate peptides to somatic mutation and major histocompatibility complex (MHC) proteins. Although deep neural networks have been primarily used for these prediction models, it is difficult to consider the models reported thus far as accurately representing the interactions between biomolecules. In this study, we propose the GraphMHC model, which utilizes a graph neural network model through molecular structure to simulate the binding between MHC proteins and peptide sequences. Amino acid sequences sourced from the immune epitope database (IEDB) undergo conversion into molecular structures. Subsequently, atomic intrinsic informations and inter-atomic connections are extracted and structured as a graph representation. Bindings are classified by feeding them into the GraphMHC network, comprising stacked graph attention and convolution layers. The prediction results from the test set using the GraphMHC model showed a high performance with an area under the receiver operating characteristic curve of 92.2% (91.9-92.5%), surpassing the baseline model. Moreover, by applying the GraphMHC model to melanoma patient data from the Cancer Genome Atlas project, we found a borderline difference in overall survival and a significant difference in stromal score between the high and low neoantigen load groups. This distinction was not present in the baseline model. This study presents the first feature-intrinsic method based on biochemical molecular structure for modeling the binding between MHC protein sequences and neoantigen candidate peptide sequences. The model can provide highly accurate suitability information for cancer patients who want to apply immune checkpoint inhibitors. Author summary

bioinformatics↗

bioRxiv2023

Translation as a Biosignature

Life on Earth relies on mechanisms to store heritable information and translate this information into cellular machinery required for biological activity. In all known life, storage, regulation, and translation are provided by DNA, RNA, and ribosomes. Life beyond Earth, even if ancestrally or chemically distinct from life as we know it may utilize similar structures: it has been proposed that charged linear polymers analogous to nucleic acids may be responsible for storage and regulation of genetic information in non-terran biochemical systems. We further propose that a ribosome-like structure may also exist in such a system, due to the evolutionary advantages of separating heritability from cellular machinery. Here, we use a solid-state nanopore to detect DNA, RNA, and ribosomes, and demonstrate that machine learning can distinguish between biomolecule samples and accurately classify new data. This work is intended to serve as a proof of principal that such biosignatures (i.e., informational polymers or translation apparatuses) could be detected, for example, as part of future missions targeting extant life on Ocean Worlds. A negative detection does not imply the absence of life; however, detection of ribosome-like structures could provide a robust and sensitive method to seek extant life in combination with other methods. One Sentence SummaryLife, defined as a chemical system capable of Darwinian evolution, likely requires an apparatus to translate heritable instructions into cellular machinery, and we propose to detect this as a biosignature of extant life beyond Earth.

biophysics↗

bioRxiv2023

Sensitivity analysis of models of gas exchange for lung hyperpolarised 129-Xe MRS and MRI.

PurposeSensitivity analysis enables the identification of influential parameters and the optimisation of model composition. Such methods have not previously been applied systematically to models describing hyperpolarised 129Xe gas exchange in the lung. Here, we evaluate current 129Xe gas exchange models to assess their precision for identifying alterations in pulmonary-vascular function and lung microstructure. MethodsWe assess sensitivity using established univariate methods and scatter plots for parameter interactions. We apply them to the model described by Patz and MOXE et al., examining their ability to measure: i) importance (rank), ii) temporal dependence, and iii) interaction effects of each parameter across healthy and diseased ranges. ResultsThe univariate methods and scatter plot analyses demonstrate consistently similar results for the importance of parameters common to both models evaluated. Alveolar surface area to volume ratio is identified as the parameter to which model signals are most sensitive. The alveolar-capillary barrier thickness is identified as a low-sensitivity parameter for the MOXE model. An acquisition window of at least 200 ms effectively demonstrates model sensitivity to most parameters. Scatter plots reveal interaction effects in both models, impacting output variability and sensitivity. ConclusionOur sensitivity analysis ranks the parameters within the model described by Patz et al and within the MOXE model. The MOXE model shows low sensitivity to alveolar-capillary barrier thickness, highlighting the need for designing acquisition protocols optimised for the measurement of this parameter. The presence of parameter interaction effects highlights the requirement for care in interpreting model outputs.

bioengineering↗