Biology subjects

Mondal, M.

Publications and source records attributed to Mondal, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Disulfide Crosslink Density is a Key Determinant in the Formation, Dynamics, and Maturation of Cysteine-rich Designer Biomolecular Condensates.

Biomolecular condensates form through weak, multivalent, non-covalent interactions, but the role of covalent crosslinks in shaping their assembly and material properties remains poorly understood. We previously showed that disulfide bonds between cysteines in designer phase-separating peptides (PSPs) act as redox-reversible crosslinks that lower the saturation concentration (Csat) and help maintain condensate fluidity. Here, we ask which sequence features govern this behavior. We built two peptide libraries: one varying the inter-cysteine spacer length (2-10 residues) and one varying cysteine density (0-33%). Inter-cysteine spacers tuned condensate properties only modestly. Longer inter-cysteine lengths raised Csat from 300 to 900 M, showed greater fluidity (as assessed by fluorescence recovery after photobleaching (FRAP) recovery rate, and resisted loss of fluidity during maturation; all inter-cysteine length variants dissolved and reformed reversibly over three redox cycles. Cysteine density, in contrast, was the dominant control parameter. Increasing cysteine density lowered Csat about 60-fold (1.5 mM to 25 M) and reduced the fluidity by an order of magnitude. Its effect on fluidity was non-monotonic: condensates with up to ~14% cysteine density stayed liquid-like for 10 days, whereas those with 21-33% cysteine density in the peptide showed slower coalescence. Condensates with the highest densities also resisted dissolution under reducing conditions and showed sharply reduced uptake of a protein cargo (eGFP; ~60% to ~9%) and a small molecule (TMR, ~70% to ~45%), consistent with smaller mesh size. Together, these results identify disulfide crosslink density as a key lever for programming condensate assembly, viscoelasticity, redox responsiveness, and porosity. The results offer key design principles both for understanding cysteine-rich disordered proteins in biomolecular condensates and for engineering redox-responsive biomaterials.

biophysics↗

bioRxiv2026

NANHA - Neurostimulation in Atypical Neurodevelopment: a Harmonized Atlas

Non-invasive brain stimulation (NIBS) has become an important tool for investigating brain function and exploring therapeutic intervention in neurodevelopmental disorders (NDDs). Nevertheless, relevant studies are scattered across different NDDs, stimulation modalities, target regions, and experimental designs, which makes systematic exploration and comparative analysis challenging. Therefore, we present NANHA, a manually curated, harmonized and freely accessible resource of published NIBS studies in NDDs. The database was constructed using systematic PubMed searches covering 22 NDDs and five NIBS modalities. NANHA captures participant characteristics, study design, stimulation purpose and parameters, targeted brain regions, behavioral, cognitive, and neurophysiological outcomes, safety information, and follow-up assessments, whenever available. The NANHA web platform (https://cb.imsc.res.in/nanha/) provides searchable and downloadable records, advanced filtering options, and interactive visualizations to support data exploration. Overall, NANHA is a standardized resource for evidence synthesis, comparative analyses, identification of research gaps, and the development of disease-specific stimulation protocols for NDDs.

neuroscience↗

bioRxiv2026

Leveraging Supramolecular Polymers to Induce the Targeted Protein Degradation of α-Synuclein

Halting the progression of neurodegenerative diseases remains one of the foremost challenges in medicinal chemistry due to the complex biology that drives disease progression. For example, a hallmark of synucleinopathies, such as Parkinsons disease, is the misfolding and aggregation of the protein -Synuclein (-Syn), driving the formation of toxic oligomers and fibrils that avoid natural intracellular clearance mechanisms, participate in unusual protein-protein interactions, and ultimately contribute to the death of dopaminergic neurons. The field of targeted protein degradation (TPD) has emerged as an innovative therapeutic route to selectively degrade proteins of interest that leverage natural intracellular protein degradation machinery. First generation TPD therapeutics have traditionally been designed as bifunctional, chimeric compounds in which a short covalent linker tethers a ligand designed to bind target proteins to a ligand that initiates an either proteosome- or lysosome-dependent protein degradation cascade. While initial studies have indicated the promise of these approaches, translation to the clinical setting has been challenging due to difficulties in achieving cellular internalization, long-term stability, and establishment of a generalizable strategy. To overcome these obstacles, this work has focused on adding modularity and dynamic capability to this classical model by leveraging a multivalent macromolecular approach to TPD. Specifically, peptide amphiphiles (PAs) were designed to self-assemble into high-aspect-ratio supramolecular nanofibers and present peptide epitopes on the surface of the fibers to target simultaneous binding of -Syn and recruitment of enzymes that facilitate entry into the lysosome-dependent chaperone-mediated autophagy protein degradation pathway. In vitro application of these bioactive PA nanofibers has demonstrated the ability to independently internalize in cells and reduce -Syn protein levels selectively and effectively. While further optimization of this model has the potential to be a viable therapeutic against -Syn aggregation, the modularity of these supramolecular nanofibers through facile monomer design and incorporation illustrates the potential of establishing a platform technology for targeting a diverse range of pathologic proteins. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/739556v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@d031adorg.highwire.dtl.DTLVardef@6d792dorg.highwire.dtl.DTLVardef@12e80c1org.highwire.dtl.DTLVardef@71a2e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Thousandfold Expansion Microscopy

Biological macromolecules, such as proteins, are made of concatenated building blocks. We hypothesized that individual protein residues could be imaged by anchoring their side chains to a swellable polymer, cleaving backbone amide bonds, and expanding residues away from each other to a degree that enables them to be visualized separately. We introduce thousandfold expansion microscopy (1000ExM), a four-network interpenetrating hydrogel architecture that enables successive expansion from [~]18-fold to >1000-fold (one billion-fold in volume). Protein and peptide structures are maintained across these expansion factors, as verified by analyses of proteins with known structures (nanobodies, GFP) and a well-studied peptide (mCLING). Computational analysis indicates that 1000ExM resolves adjacent amino acid residues, thereby achieving sub-nanometer precision on conventional light microscopes. We anticipate that 1000ExM will find wide utility in protein visualization and identification, potentially even in intact cells and tissues.

molecular biology↗

bioRxiv2026

Sustained presence of metabolically active mesophiles in the boiling vent-water of a low-salinity, slightly-alkaline, sulfate-rich geothermal spring characterized by an inequitable ecology of hyperthermophiles and thermophiles

Geothermal vent-heads exclusively support the proliferation of (hyper)thermophilic microorganisms. However, diverse mesophiles are stochastically thrust into these ecosystems by local geodynamic forces, and their population-level responses to the unfamiliar stressor hold critical implications for lifes intrinsic resilience to biophysical adversities. Here, we report a time-course exploration of the boiling vent-water of a Trans-Himalayan geothermal spring to determine the population dynamics, in situ functionalities, and potential ecological roles of mesophilic incomers in the context of indigenous (hyper)thermophiles. The temporally-consistent (hyper)thermophilic core-community, predominated in turn by a few Aquificia and Thermoproteota, was delineated as metagenome-assembled genomes. Mesophiles/moderate-thermophiles were identified as MAGs and/or pure-cultures, and whether temporally-consistent/inconsistent, had far lower prevalence. Overall, in situ transcriptional activity and prevalence had significant positive correlation; but many species exhibited high activity despite low prevalence and vice versa, implicating the decoupling of global metabolism from growth/proliferation. Bulked metatranscriptomic signatures identified the (hyper)thermophiles as primary producers of the ecosystem. Populations of mesophiles and moderate-thermophiles were apparently active, but not growing, in situ, with some being engaged in environment detoxification, and production of nutrients, metabolites and protective-biomolecules wanting in the (hyper)thermophiles. The findings engender an unprecedented portrayal of geothermal-vents as multi-community ecosystems where unfamiliar immigrants provide critical metabolic services.

microbiology↗

bioRxiv2026

LinkDTI: Drug-Target Interactionsprediction through a Link Predictionframework on Biomedical KnowledgeGraph

Computational drug-target interactions (DTI) prediction serves as a valuable tool for drug discovery and repurposing by cost-effectively narrowing down the potential drug-target space. This paper presents LinkDTI, a computational framework that predicts DTIs by identifying connections within a heterogeneous knowledge graph of drugs, proteins, diseases, and side effects. Unlike methods that rely on mathematical techniques like matrix completion or similarity-based scoring, LinkDTI uses an advanced graph-based approach to capture relationships between biomedical entities. Specifically, LinkDTI applies a modified version of the multilayer GraphSAGE model that learns from the heterogeneous knowledge graph and predicts potential drug-target interactions. Our model incorporates negative sampling that balances the data to address the issue of having more negative than positive interactions. Our results show that LinkDTI consistently performs better in AUROC and AUPRC than baseline methods by at least 2.5% across different sampling ratios and conditions. Subsequently, it identifies approximately 945 new potential DTIs, marking a 49.14% increase over known DTIs. Overall, LinkDTI offers a simple yet effective method for integrating diverse biomedical data to identify potential drug-target interactions. The code and data can be found at https://github.com/hub2nature/LinkDTI_heterogenous_KG.git.

bioinformatics↗

bioRxiv2025

A Highly Thermostable and Novel GH5 Endoglucanase from Bacillus sp. Strain BS with Enhanced Biomass Saccharification Potential in Seawater

The efficient enzymatic conversion of lignocellulosic biomass to glucose is crucial for biofuel production, with enzyme costs being a significant barrier to commercialization. Multifunctional enzymes that reduce enzyme components can improve efficiency. In this study, we amplified and sequenced a gene from Bacillus sp. strain BS, which showed 89.8% identity with bacterial endoglucanase Q6YK34. This putative novel endoglucanase, BsEG2, is a GH5-like endoglucanase, with optimal activity at pH 6.0 and 55 {square}, and efficiently hydrolyzes amorphous and crystalline cellulose, including pre-treated and untreated sugarcane bagasse. Kinetics on carboxymethyl cellulose (CMC) indicate high substrate binding efficiency (apparent Vmax of 148.9 {micro}M min-1, a Km of 24.9 mg mL-1, and a kcat of 517 s-1). BsEG2 hydrolyzes long cellulosic chains, oligosaccharides, and cellobiose to produce glucose, demonstrating multifunctionality. It exhibits remarkable thermal stability, retaining over 90% activity after 15 days at 55 {degrees}C. BsEG2 also retains activity in high salts and ionic liquids, and is not inhibited by cellobiose, even at 200 mM, unlike other endoglucanases and cellobiohydrolases. Furthermore, BsEG2 functions in seawater, reducing freshwater footprint in biofuel production. BsEG2 is a promising candidate for a cost-effective enzyme formulation for glucose production from lignocellulosic biomass, supporting downstream glucose-fed metabolic pathways.

biochemistry↗

bioRxiv2025

IntegrateALL: an end-to-end RNA-seq analysis pipeline for multilevel data extraction and interpretable subtype classification in B-precursor ALL

Transcriptome sequencing (RNA-seq) is emerging as a diagnostic standard for B-cell precursor acute lymphoblastic leukemia (B-ALL). Expression-based classifiers reach [~]95% accuracy, but reproducible end-to-end solutions that also integrate transcript-derived genomic drivers and quantitative virtual karyotyping are lacking. We developed IntegrateALL, a Snakemake pipeline that standardizes RNA-seq analysis from FASTQ to rule-based subtype assignment across 26 WHO-HAEM5/ICC entities by integrating expression-based subtype prediction, gene fusion- / hotspot SNV calling and virtual karyotyping. We introduce KaryALL, a machine-learning classifier that uses normalized expression and minor-allele-frequency features (RNASeqCNV) to distinguish near haploid, hypodiploid and high hyperdiploid B-ALL and chromosome-21 gains/iAMP21 (accuracy: 0.98 / F1-score: 0.96 on 615 independent test samples). SNP-array concordance supported RNA-based karyotyping. Applied to 774 unselected B-ALL cases, IntegrateALL yielded unambiguous subtype assignments in 81.5%, based on concordance of gene expression class with a defining driver (75.3% of all cases) or, in selected cases, high-confidence expression-based classification alone (6.2%); the remainder (18.5%) were flagged for manual curation. Independent validation (3 cohorts; n=436, including pediatric cases) reproduced these distributions. Across all patients (n=1,210), 2.6% harbored two subtype defining drivers, including hyperdiploidy in fusion-driven subtypes where it was not expected or subtype-defining SNVs (e.g., PAX5 P80R / IKZF1 N159Y) co-occurring with BCR::ABL1-positive/-like, KMT2A- or DUX4-fusions. In most dual-driver cases, one subtype gene expression signature predominated, indicating a hierarchy of oncogenic control and the value of systematic driver screening alongside expression-based calls. IntegrateALL provides an adaptable fully reproducible workflow for molecular B-ALL characterization by systematically integrating genomic drivers and downstream gene regulation.

cancer biology↗

bioRxiv2025

SAM-DTI: A Spatial Attention Model for Drug-Target Interaction Prediction

Drug-target protein interaction (DTI) prediction is an important area of research in drug repurposing and discovery. Laboratory experiments for exploring DTI space need a lot of time and money due to the high volume of potential compounds. The past decades advancements in deep learning have made progress in efficient prediction of DTIs. This paper proposes a spatial attention model for predicting drug-target interactions (SAM-DTI) from labeled SMILES strings and protein sequences. SAM-DTI (i) tries to encapsulate the input features with more relevance to the biological binding of drug-target interactions, rather than models that solely extract features from individual inputs, and (ii) emphasizes giving dynamic importance to each pair of drug-target interactions. The model follows a knowledgeinspired sub-structure vocabulary to preprocess the inputs. It predicts accurate DTI values from the interactions between each SMILES sub-structure and protein substructure pair. SAM-DTI achieves competitive performance compared to state-of-the-art methods.

bioinformatics↗

bioRxiv2025

Psychrophilic and cryophilic bacterial copiotrophs from a Trans-Himalayan lake-desert ecosystem as biogeothermometers of warming, mitigators of perturbation, and candidates for biodegradation

A Trans-Himalayan lake-desert ecosystem was explored for the low-to-high temperature adaptations of native copiotrophic psychrophiles that have the potentials for rendering substantive carbon remineralization under natural and/or anthropogenically influenced conditions of high organic matter delivery to the environment. Overall 27 species, classified across 15 genera of Actinomycetota, Bacillota, Bacteroidota, and Pseudomonadota, were isolated from the brackish-water and sediment-surface of Tso Moriri (a massive lacustrine body on the Changthang plateau that remains frozen for approximately one third of the year), and the fine talus covering a lake-side rocky mountain. In Luria broth, all the isolates grew at 4{degrees}C and 15{degrees}C; 13 of them grew, while 14 retained 19-99% cells in metabolically-active state, at -10{degrees}C; 23, 11, and none grew at 28{degrees}C, 37{degrees}C, and 42{degrees}C respectively. A Cryobacterium was most heat-susceptible, whereas some -10{degrees}C-growing Arthrobacter, Microbacterium, Paenarthrobacter, Pseudomonas and Streptomyces were most warming-resilient, among the present isolates. Catabolizing different simple/complex organic compounds, all isolates accomplished low/moderate/high growths at 4{degrees}C; 20 performed low growths at -10{degrees}C. Taxonomy/phylogeny did not determine the isolates growth/survival across the temperature-range tested. Lake-water and rock-dust isolates had the widest, while lake-sediment-dwellers had the narrowest, temperature-window for growth/survival. Rock-dust and lake-water isolates had more genes for low and high temperature adaptations, compared to the lake-sediment isolates. In co-cultures, most actinobacterial isolates inhibited the growth of mesophilic bacteria from warmer ecosystems, plus non-actinobacteria and actinobacteria from native/adjoining habitats. The data hold implications for biodegradation in cold/frigid territories, negative feedback control/reversal of warming, and microbiome protection from infiltration amidst climate change. IMPORTANCEPhylogenetically diverse, cold-adapted copiotrophic bacteria were retrieved from a Trans-Himalayan lake-desert ecosystem, and tested for chemoorganoheterotrophic growth at temperatures between -10{degrees}C and 42{degrees}C. Albeit growth dwindled at [≥]28{degrees}C, most of the isolates thrived on simple as well as complex organic substances under freezing condition, which makes them prospective constituents of biodegradation reactors suitable for high-altitude/latitude deployment. In the natural habitats of the psychrophilic isolates, cessation of organotrophic activities at elevated temperatures would stop simple fatty acids and CO2 production, which in turn would preempt methanogenesis, undo greenhouse effect, and reverse environmental thawing (usher cooling). Such negative feedback control of homeostasis is fraught with the danger of microbiome takeover by thermally-better-adapted foreign organisms. Consequently, ecosystem preservation rests on the native microfloras ability to resist external invasion. At 28{degrees}C, majority of the actinobacterial isolates inhibited bacteria from discrete higher-temperature ecosystems; they can, therefore, be viewed as the defenders of the cold/frigid ecosystem.

microbiology↗

bioRxiv2025

Intra-subtype heterogeneity shapes treatment response in KMT2A-rearranged ALL across all age groups

BackgroundKMT2A-rearranged B-cell acute lymphoblastic leukemia (KMT2Ar B-ALL) exhibits significant heterogeneity in age of onset, developmental origins, and clinical outcomes. The interplay of individual factors influencing early treatment response within this high-risk molecular subtype remains poorly elucidated. We aimed to comprehensively assess how leukemic developmental state, fusion partner, and patient age jointly influence early treatment response and drug sensitivity. MethodsTo identify determinants of early treatment response to induction chemotherapy, we analysed 465 KMT2Ar B-ALL cases spanning a wide age range (1 month to 89 years) by integrating transcriptomic and genomic profiling with functional drug response and measurable residual disease (MRD) kinetics. Transcriptomic profiling was used to derive a developmental maturity score based on proximity to physiological B-cell differentiation from a normal B-lymphopoiesis reference. Using an ordinal regression model we identify gene expression programs associated with early MRD response. ResultsWe observed a strong inverse correlation between MRD clearance with advancing age (p=2.1E-04), proximity to early B-cell-precursor developmental state (low maturity score, p=1.3E-03) and AFF1 as fusion partner (p=7.0E-04). A combined model confirmed the predominate impact of both maturity and KMT2A fusion partner on MRD response, supporting the concept that the cells developmental state defines therapy response. Gene expression analysis identified cellular traits that relate to MRD response (e.g. chromatin organization, immune modulation and proliferation). This gene expression classifier grouped cases by MRD response but also by ex-vivo induction drug sensitivity. Notably, good responders to ex-vivo induction drugs were characterized by a higher maturity score (p=1.8E-03), whereas for less mature KMT2Ar B-ALL cases response profiles suggested higher Venetoclax sensitivity. ConclusionsOur study provides an integrative framework linking developmental phenotype, fusion partner, and MRD kinetics across the full age spectrum of KMT2Ar B-ALL. The maturity score, derived from bulk transcriptome data, offers a biologically relevant predictor of early treatment response and drug sensitivity. These insights may support future risk-adapted strategies and therapeutic targeting, particularly in immature KMT2Ar B-ALL.

cancer biology↗

bioRxiv2025

Node persistence from topological data analysis reveals changes in brain functional connectivity

Large-scale analyses of brain functional connectivity can uncover disruptions in regional activity and connectivity that are commonly associated with neurological disorders or cognitive decline associated with healthy aging. In our study, we employ persistent homology (PH), a prominent tool in topological data analysis (TDA), to investigate changes in resting-state functional connectivity in healthy aging and autism spectrum disorder (ASD). We analyze functional connectivity changes across three distinct scales: (a) global scale (brain-wide changes), (b) mesoscopic scale (resting-state network-level changes), and (c) local scale (region-level changes). At the local scale, we introduce node persistence, a novel and scalable PH-based measure that detects brain regions with significant differences in healthy aging or ASD. Notably, these regions overlap with regions whose non-invasive stimulation improves motor function in the elderly or alleviates ASD symptoms, suggesting the utility of node persistence in identifying clinically relevant brain regions affected by aging and ASD.

neuroscience↗

bioRxiv2025

Disulfide cross-linked redox-sensitive peptide condensates are efficient cell delivery vehicles of molecular cargo.

Biomolecular condensates (BCs) are phase-separated viscoelastic hubs within demixed solutions enriched in proteins and nucleic acids. Such condensates, also called membraneless organelles, are increasingly observed in cells and serve as transient hubs for spatial organization and compartmentalization of biomolecules. Along with the transiency of formation and dissolution, their ability to sequester molecules has inspired us to develop BCs as potential vehicles to transport and deliver molecular cargo. We recently reported the design of disulfide bond cross-linked phase-separating peptide (PSP) condensates that spontaneously dissolve in reducing conditions (JACS, 2024, 146, 255299). Based on the premise that the highly reducing cytoplasm could dissolve PSP condensates and release partitioned cargo, here, we demonstrate the ability of PSP condensates to deliver molecular cargo to the cytoplasm of HeLa cells efficiently. We show that PSP condensates deliver a variety of cargos that differ in their sizes and chemistries, including small molecules, peptides, GFP protein (31 kDa), DNA (1.7 kbp), and mRNA. The transfection efficiencies of PSP condensates for delivering DNA and mRNA were also significantly greater than those of a commercial transfection agent. With room to tailor the condensate properties based on cargo and cell types, these results showcase the potential of disulfide-cross-linked PSPs as effective and customizable cellular delivery vehicles, filling a critical demand gap for such delivery systems.

biophysics↗

bioRxiv2025

Targeting Colorectal Cancer Liver Metastasis Through Repurposing Metabolic and Immune Inhibitors : A Theoretical Study

Liver metastasis from colorectal cancer is a major cause of death in patients with advanced colorectal cancer (CRC) and remains a difficult challenge in oncology. Inspite of commnedable developments in medical inventions, the complexity and poor prognosis of metastatic stage, alliterative strategies are required to address Colorectal cancer liver metastasis (CRLM). This paper presents a computational study on drug repurposing for CRLM using a Boolean Network model. We comprehensively analyze CRLM signaling pathways such as WNT, PI3K/AKT/mTOR, MAPK, Hedgehog, TGF-{beta}, NF-kB, NOTCH and HGF and target them with metabolic and immune inhibitors. This study utilizes a computational analysis to evaluate single and multi-agent treatments across scenarios involving single and multiple genetic mutations. Our findings highlights the efficacy of metabolic inhibitors such as Simvastatin, Metformin, and predict compatible partner drugs to enhance their effiacy. Additionaly, we predict possible improvements for CRLM treatment using an immunotherapy drug like Pembrolizumab. Overall, this paper provides new insights into drug repurposing to improve CRLM treatment outcomes.

cancer biology↗

bioRxiv2025

Particular Amino Acid on Lateral Interface Maintains FtsZ Function Under Acid Stress in Streptococcus mutans

FtsZ is the core protein for cell division in bacteria that can polymerize into Z-rings and drive cytokinesis. Understanding how bacteria maintain the correct function of FtsZ under various environmental stresses is crucial for novel antibacterial drug discovery. Our previous study revealed that the FtsZ in S. mutans has higher self-assembly and GTPase activity under acidic stress, which may be responsible for the cariogenesis of S. mutans. However, the mechanism is still unknown. Here, we further reported the crystal structure of S. mutans FtsZ, revealing a unique lateral interface. Through protein polymerization and GTPase ability assay, we experimentally demonstrated that mutation of Arg68 on this lateral interface significantly reduced the functional activity of FtsZ in an acidic environment. The phenotype assay and rat caries model further showed that mutation of Arg68 effectively inhibited the acid resistance of S. mutans and the occurrence and progress of dental caries in vivo. By employing a molecular dynamics simulation analysis, we conclude that mutation of Arg68 disrupts the conformation change necessary for SmFtsZ polymerization under acidic conditions. Our study proposes a novel mechanism to maintain FtsZ function in bacteria and could be a potential target for antimicrobial drugs to inhibit the growth of S. mutans in an acidic environment. Significance StatementFtsZ is the core protein that drives cytokinesis. Maintaining the self-assembly and GTPase activity of FtsZ plays a critical role in cell growth under environmental stress. Currently, research on FtsZ function maintenance under stress mainly focuses on model organisms, with less on other pathogenic bacteria. This study reveals a novel structural mechanism for the acidic tolerance of FtsZ in S. mutans which survives in strongly acidic surroundings. Meanwhile, Arg68 on the lateral interface of SmFtsZ may be a potential therapeutic target to regulate microecology and combat S. mutans-associated dental caries.

microbiology↗

bioRxiv2024

Resolving out of Africa event for Papua New Guinean population using neural network

The demographic history of the Papua New Guinean population is a subject of significant interest due to its early settlement in New Guinea, at least 50 thousand years ago, and its relative isolation compared to other out of Africa populations. This isolation, combined with substantial Denisovan ancestry, contributes to the unique genetic makeup of the Papua New Guinean population. Previous research suggested the possibility of admixture with an early diverged modern human population, but the extent of this contribution remains debated. This study re-examines the demographic history of the Papua New Guinean population using newly published samples and advanced analytical methods. Our findings demonstrate that the observed shifts in relative cross coalescent rate curves are unlikely to result from technical artefacts or contributions from an earlier out of Africa population. Instead, they are likely due to a significant bottleneck and slower population growth rate within the Papua New Guinean population. Our analysis positions the Papua New Guinean population as a sister group to other Asian populations, challenging the notion of Papua New Guinean as an outgroup to both European and Asian populations. This study provides new insights into the complex demographic history of the Papua New Guinean population and underscores the importance of considering population-specific demographic events in interpreting relative cross coalescent rate curves.

evolutionary biology↗

bioRxiv2024

Interaction with AK2A links AIFM1 to cellular energy metabolism

Apoptosis inducing factor 1 (AIFM1) is a flavoprotein essential for mitochondrial function and biogenesis. Its interaction with MIA40, the central component of the mitochondrial disulfide relay, accounts for some, but not all effects of AIFM1 loss. Our high-confidence AIFM1 interactome revealed novel interaction partners of AIFM1. For one of these interactors, adenylate kinase 2 (AK2), an essential enzyme maintaining cellular adenine nucleotide pools, AIFM1 binding specifically stabilized the isoform AK2A via interaction with its C-terminus. High resolution cryo-EM and biochemical analyses showed that both, MIA40 and AK2A bind AIFM1s C-terminal {beta}-strand, enhancing NADH oxidoreductase activity by locking an active, dimer conformation and, in the case of MIA40, affecting the cofactor binding site. The AIFM1-AK2A interaction is crucial during respiratory conditions. We further identified ADP/ATP translocases and the ATP synthase as AIFM1 interactors, emphasizing its important regulatory role as a central, organizing platform in energy metabolism.

biochemistry↗

bioRxiv2024

Amyloid peptide - synthetic polymer blends with enhanced mechanical and biological properties

Interest in utilizing amyloids to develop biomaterials is increasing due to their potential for biocompatibility, unique assembling morphology, mechanical stability, and biophysical properties. However, challenges include the complexity of peptide chemistry and the practical techniques required for processing amyloids into bulk materials. In this work, two decapeptides with fibrillar and globular morphologies were selected, blended with poly(ethylene oxide), and fabricated into composite mats via electrospinning. Notable enhancements in mechanical properties were observed, attributed to the uniform distribution of the decapeptide assemblies within the PEO matrix. Morphological differences, such as the production of thinner nanofibers, are attributed to the increased conductivity from the zwitterionic nature of the decapeptides. Blend rheology and post-processing analysis revealed how processing might affect the amyloid aggregation and secondary structure of the peptides. Both decapeptides demonstrated good biocompatibility and strong antioxidant activity, indicating their potential for safe and effective use as biomaterials. By evaluating these interdependencies, this research lays the foundation for understanding the structure-property-processing relationships of peptide-polymer blends and highlights the strong potential for developing applications in biotechnology.

biophysics↗