Biology subjects

Acharya, S.

Publications and source records attributed to Acharya, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

The genetic origin of fetal growth restriction and mitochondrial complex I dysregulation

BackgroundMitochondria are organelles required for bioenergetic homeostasis, providing energy in the form of ATP to support cellular function, growth, and proliferation. Mitochondria synthesise ATP using the electron transport chain (ETC) to produce an electrochemical gradient that facilitates the conversion of ADP to ATP by ATP synthase. Mitochondrial function is governed by an intricate bidirectional relationship between the mitochondrial genome encoding 1-2% of proteins and the nuclear genome which encodes 98-99% of mitochondrial proteins. Pregnancy creates a unique environment whereby the mitochondrial genome of the placenta is maternally inherited, while the nuclear genome is comprised of both maternal and paternal contributions. Thus, mitochondrial structure and function are largely dependent on the adaptability of mitochondria to conform to the new mixed nuclear genome. In pregnancy, fetal growth restriction (FGR) is characterised by poor placental development, underlying trophoblast insufficiencies, and is associated with mitochondrial dysfunction within the placenta, although the mechanisms which underpin these changes remain unclear. This study investigated if mitochondrial dysfunction in FGR is programmed by genetic incompatibility arising from single nucleotide polymorphisms (SNPs). Methods and findingsWe performed a targeted meta-analysis of over 100 genome wide association studies within the early growth genetics (EGG) consortium, assessing 289 genes encoding mitochondrial function across the ETC and ATP synthase. This study identified 37 SNPs across 32 genes associated with low birthweight. Sanger sequencing was performed to validate the presence of 10 SNPs of interest located within the nuclear genome in a cohort of fetal growth restricted placentas. Of the 10 SNPs assessed we confirmed the presence of 6 in FGR, and identified an additional previously unidentified SNP, and detected 3 nucleotide deletions across numerous components of the electron transport chain. This analysis identified 5 mutations within genes that encode complex I. Subsequent analysis of the gene and proteins that correspond to complex I mutations was performed using PCR, proteomics, and western blotting. Notably, we identified significant downregulation of NDUFA6 at the gene and protein level in FGR, lower protein levels of NDUFS3 and NDUFS6, and confirmed the largest log2 fold change identified in NDUFS6 by western blot. Subsequent investigation of mitochondrial respiratory capacity identified decreased ATP-linked respiration in FGR using Seahorse XF Analysis. ConclusionOur results identify that there is an inheritable contribution of SNPs within the maternal and paternal nuclear genome in fetal growth restriction. These SNPs alter gene expression and protein abundance of mitochondrial complex I components, impacting structural assembly and subsequent bioenergetic function within the placenta. Collectively these findings suggest that SNPs that affect mitochondrial assembly and function are associated with low birthweight and fetal growth restriction.

developmental biology↗

bioRxiv2025

Placental Iron Utilisation in Fetal Growth Restriction: Alterations in Mitochondrial Heme Synthesis and Iron-Sulfur Cluster Assembly Pathways

Fetal growth restriction (FGR) affects [~]10% of pregnancies worldwide and is often associated with placental insufficiency. Iron is essential for maternal haematopoietic adaptations and placental processes such as mitochondrial iron-sulfur (Fe-S) cluster assembly, heme synthesis, and erythropoiesis. This study aimed to characterise iron transport and downstream utilisation in FGR. Placental tissues from term uncomplicated (n=19) and FGR (n=18) pregnancies were analysed. Maternal iron status was retrospectively assessed from clinical records. Placental mRNA and protein expression of iron-dependent pathways were analysed via RT-qPCR, LC-MS, and western blotting. Placental iron content was assessed histologically, and heme levels were measured by activity assay. FGR pregnancies showed significantly elevated maternal serum ferritin and lower red cell distribution width, although remained within normal clinical values. Placental iron uptake transporters TFRC and DMT1 were significantly upregulated, while the iron exporter to the fetus, ferroportin, was reduced, indicating increased iron retention in the FGR placenta. Despite altered transporter expression, Fe3 iron levels were unchanged, suggesting iron utilisation over storage. Subsequent investigations identified reduced mitochondrial Fe-S synthesis components (FDXR, FDX2, NDUFAB1, HSPA9), and a prioritisation of mitochondrial and cytosolic heme synthesis enzymes in FGR. Protein levels of haemoglobin subunits (HBG1, HBG2, HBB, HBA1) and erythrocyte membrane markers (EPB41, EPB42, SPTA1, SPTB, ANK1) were decreased. These findings reveal a compensatory response in FGR placentae, with increased iron uptake and utilisation favouring heme synthesis over Fe-S cluster formation, possibly to support oxygen handling under poor placental vascularisation and reduced fetal oxygenation, with potential consequences for mitochondrial energy metabolism. Key PointsO_LIIron plays a critical role in placental function, while iron-dependent pathway components are well-characterised, their integrated response and adaptive reprogramming in fetal growth restriction (FGR) remain poorly understood. C_LIO_LIIn FGR, maternal iron status was unchanged, however, placental iron uptake proteins were increased and ferroportin reduced, suggesting that the placenta retains iron. C_LIO_LIFGR placentae showed altered de novo mitochondrial iron-sulfur cluster (Fe-S) formation and a bottleneck in late-stage Fe-S cluster assembly. C_LIO_LIThis shift in Fe-S synthesis prioritises mitochondrial and cytosolic heme synthesis pathways, consistent with increased heme utilisation and breakdown. C_LIO_LIGlobin subunits were lower in protein abundance and impaired placental erythrocyte structure in FGR. C_LIO_LIDysregulation of erythrocyte membrane proteins in FGR placentae suggests altered erythrocyte structure, potentially representing an adaptive response to inadequate vascularisation, attempting to optimise oxygen delivery to the fetus. C_LI

physiology↗

bioRxiv2025

Electron tomography reveals mitochondrial network and cristae remodelling during cell differentiation in the human placenta

Mitochondria adapt their structure through fusion and fission, yet how their morphology and cristae architecture alter as cells differentiate remains unclear. The human placenta is an ideal model for studying mitochondrial diversity within a single tissue. As epithelial trophoblast cells of the placenta differentiate, their accompanying mitochondria morphologically and functionally transform. We used array tomography to characterise mitochondrial volume and network complexity. Cryo-electron tomography revealed two distinct subpopulations of mitochondria within progenitor cytotrophoblasts, and a singular, homogeneous population in the differentiated syncytiotrophoblast. We showcased the 3D topology of individual cristae through a standardised metric of "curvedness". Proteomic analysis of isolated mitochondria identified reduced dynamics proteins and cristae organisation complexes, accompanied by subunit variations within the electron transport chain, ATP synthase, and altered supercomplex abundance. This study highlights the advantages of combining multimodal imaging with mechanistic insights, to elucidate the process of mitochondrial morphology and cristae architecture remodelling as cells differentiate.

cell biology↗

bioRxiv2025

SynGAP forms biocondensates at sub-micromolar concentrations and recruits PSD95 and receptor oligomers, functioning as a key initiator of PSD formation

A key issue in neuronal circuit regulation is how synapse formation is initiated. Synapse formation could start when one or more synaptic scaffold proteins that can initiate synapse formation reach certain threshold concentrations in the dendritic shaft, which might lead to their oligomerization or even liquid-liquid phase separation (LLPS). By combining in vitro reconstitution of purified proteins with live-cell single-molecule and confocal imaging, we demonstrated that SynGAP alone forms assemblies of nanoscale clusters containing several to several tens of molecules at 10-nM order concentrations and micron-scale LLPS hydrogel-like condensates at submicromolar concentrations. The trimers of SynGAP's intrinsically disordered region (IDR) induced by its coiled-coil domain are responsible for SynGAP condensation. CaMKII-mediated phosphorylation moderately suppresses SynGAP condensation, and also increases condensate liquidity. While PSD95 fails to form assemblies under these conditions, it is recruited to SynGAP condensates by specifically binding to the PDZ-binding motif of SynGAP. SynGAP[PSD95] condensates selectively immobilize postsynaptic transmembrane proteins, Neuroligin1 and AMPAR-TARP2 complexes, in a manner dependent on their oligomerization state, indicating cooperative recruitment dynamics among SynGAP, PSD95, and transmembrane components, which might mimic initial PSD assembly. These findings suggest that SynGAP may act as a primary nucleator of postsynaptic density assembly, challenging the PSD95-centered models.

neuroscience↗

bioRxiv2025

Epigenetic and Transcriptomic Alterations Precede Amyloidosis in the Hippocampus of the Alzheimer's Disease AppNL-G-F Knock in Mouse Model

Detecting and understanding the early stages of Alzheimers disease (AD) is essential for uncovering initial mechanisms of neuropathology and devising effective interventions. In this study, we leveraged the humanized AppNL-G-F mouse which exhibits early-onset amyloid pathology with a predictable timeline, to investigate molecular changes in the hippocampus and blood before the onset of severe neuropathology and independent of aging. Employing a multi-omics approach, we identified alterations in chromatin accessibility, gene expression, and DNA methylation associated with early amyloidosis. Chromatin accessibility changes were prominent in excitatory neurons during early pathology, with a later shift to inhibitory neurons, potentially reflecting compensatory mechanisms to mitigate excitatory neuron dysregulation. Despite broadly comparable hippocampal cell composition, transcriptomic comparisons between wild-type and AppNL-G-F mice revealed major gene expression differences, particularly in pathways related to mitochondrial function and protein biosynthesis, preceding severe amyloid plaque deposition. In later stages, upregulation of immune and neuroinflammatory pathways was observed, aligning with established neuroinflammatory processes in AD. Additionally, we identified extensive DNA methylation differences in both the blood and hippocampus of AppNL-G-Fmice during early and late stages of pathology. Many differentially methylated regions in the blood, even at early pathology stages, were associated with cis-regulatory elements in the brain and were located near differentially expressed genes in the hippocampus. These regions were enriched in pathways associated with brain function, including neuron development and synaptic processes, highlighting a connection between blood methylation patterns and brain activity. This finding suggests the potential use of blood DNA methylation as a biomarker for the early detection of amyloidosis. Notably, we identified five candidate biomarker genes, including Rbfox1 and Camta1, with epigenetic dysregulation detectable in both the brain and blood prior to severe amyloid accumulation. Our study, leveraging a unique AD mouse model and a multi-omics approach, highlights epigenetic signatures of AD before the onset of clinical symptoms, providing a foundation for future research into early diagnosis and therapeutic strategies, as well as potential blood biomarkers.

molecular biology↗

bioRxiv2025

Phenethylaminylation: Preliminary In Vitro Evidence for the Covalent Transamidation of Psychedelic Phenethylamines to Glial Proteins using 3,5-Dimethoxy-4-(2-Propynyloxy)-Phenethylamine as a Model Compound

Psychedelics are well known for their ability to produce profoundly altered states of consciousness. But, more importantly, the effects of psychedelics can influence neurobehavioral changes that last well after these acute subjective effects end. This phenomenon is currently being leveraged in the development of psychedelic-assisted psychotherapies for the treatment of multiple neuropsychiatric disorders. The cellular and molecular mechanisms by which single doses of psychedelics are able to mediate long-term cognitive changes are an active area of research. We hypothesize that psychedelics contribute to long term changes in cellular state by covalently modifying proteins. This post-translational modification by psychedelics is possible through the transglutaminase-mediated transamidation of their amine termini to glutamine carboxamide residues. Here, we synthesize and utilize a propargylated analogue of mescaline - the classic serotonergic psychedelic phenethylamine found in cacti species - to identify putative protein targets of psychedelic modifications through the use of click-chemistry in a primary human astrocyte cell culture model. Our preliminary findings indicate that a diverse array of glial proteins may be substrates for transglutaminase 2-mediated monoaminylation by our model phenethylamine ("phenethylaminylation"). Based on these points, we speculatively highlight new directions for the study of this putative noncanonical psychedelic activity.

molecular biology↗

bioRxiv2025

FISHNET: A Network-based Tool for Analyzing Gene-level P-values to Identify Significant Genes Missed by Standard Methods

FISHNET uses prior biological knowledge, represented as gene interaction networks and gene function annotations, to identify genes that do not meet the genome-wide significance threshold but replicate nonetheless. Its input is gene-level P-values from any source, including omicsWAS, aggregation of GWAS P-values, CRISPR screens, or differential expression analysis. It is based on the idea that genes whose P-values are low due to sampling error are distributed randomly across networks and functions, so genes with suggestive P-values that cluster in densely connected subnetworks and share common functions are less likely to reflect sampling error and more likely to replicate. FISHNET combines network and function analysis with permutation-based P-value thresholds to identify a small set of exceptional genes that we call FISHNET genes. Applied to 11 cardiovascular risk traits, FISHNET identified 19 gene-trait relationships that missed genome-wide significance thresholds but, nonetheless, replicated in an independent cohort. The replication rate of FISHNET genes matched or exceeded that of other genes with similar P-values. FISHNET identified a novel association between RUNX1 expression and HDL that is supported by experimental evidence that RUNX1 promotes white fat browning, which increases HDL cholesterol levels. FISHNET also identified an association between LTB expression and BMI that is supported by experimental evidence that higher LTB expression increases BMI via activation of the LT{beta}R pathway. Both associations failed genome-wide significance thresholds, highlighting FISHNETs ability to uncover meaningful relationships missed by traditional methods. FISHNET software is freely available at https://doi.org/10.5281/zenodo.14765850.

bioinformatics↗

bioRxiv2025

Construction of Multi-Modal Transcriptome-Small Molecule Interaction Networks from High-Throughput Measurements to Study Human Complex Traits

We present Gene-Embedded Multi-modal Networks (GEM-Net), a semi-supervised framework for constructing multi-modal networks centered on genes. GEM-Net uses gene-level modules and selectively incorporates heterogeneous omics profiles using a correlated meta-analysis strategy that accounts for scale imbalance, missingness, and intra-modular correlation. Prior to network inference, we developed a harmonized data processing protocol that adjusts each omic layer independently through a shared mathematical workflow involving transformation, dimensionality reduction, and regression-based covariate adjustment. GEM-Net modules were inferred and benchmarked against unsupervised methods using transcriptomic, metabolomic, and lipidomic data from the Long Life Family Study (LLFS), a unique cohort enriched for exceptional familial longevity and health. GEM-Net modules were more diverse and biologically interpretable, with stronger support from protein- protein interactions, transcriptional regulation, and metabolic annotations. Applying GEM-Net to metabolic health in LLFS revealed an axis between the microbiome-derived metabolite N-acetylglycine and immune genes (FCER1A, HDC, CPA3, MS4A2) associated with improved insulin sensitivity and reduced inflammation in healthy older individuals. GEM-Nets offer a reusable reference from a long-lived population and a generalizable framework for multi-omics discovery. https://doi.org/10.5281/zenodo.15003731.

systems biology↗

bioRxiv2024

The sugar beet root maggot, Tetanops myopaeformis transcriptome sample statistics in relation to it experiencing susceptible and resistant reactions with sugar beet, Beta vulgaris ssp. vulgaris

The sugar beet root maggot (SBRM), Tetanops myopaeformis (von Roder), is a devastating insect pathogen of sugar beet (SB), Beta vulgaris ssp, vulgaris (B. vulgaris), one of only two plants in the world from which significant global raw sugar is produced, $1 billion, U.S., $4.6 B, globally. Experiments reveal the SBRM larval transcriptome experiencing two different susceptible or resistant responses by sugar beet SBRM larvae were sampled at time = 0 hours post infection [hpi]), prior to being introduced to B. vulgaris and after infection on F1016 and F1024 (resistant), and F1010 and L19 (susceptible) for 24, 48, and 72 hpi when the larvae were removed for transcriptomic analysis. The transcriptomic analyses included determining the number of reads per sample, mapping the transcripts to the recently sequenced SBRM TmSBRM_v1.0 draft genome, identifying genes that relate to the resistant and susceptible responses. Moreover, the RNA-seq experiments provide data for generating differential expression analyses between the various sample types, thus, yielding an understanding SBRM biology, the development of new control strategies for this pathogen, relationship to model genetic organisms like Drosophila melanogaster, relationship to pathogenic non-model organisms, and aid in agronomic improvement of sugar beet for stakeholders.

genomics↗

bioRxiv2024

Stabilized marker gene identification and functional annotation from single-cell transcriptomic data

With the rapid emergence of single-cell transcriptomics datasets, reproducible marker genes and functional annotation of cell type or state is becoming increasingly important. Conventional methods that rely on differential gene expression (DEG) analysis lack both consistency across datasets and functional annotations of selected markers. Here, we present scSCOPE, an R- based platform that utilizes stabilized LASSO (Least Absolute Shrinkage and Selection Operator) feature selection, bootstrapped co-expression networks, and pathways enrichment to identify reproducible and functionally relevant marker genes and associated pathways for cell type identification and functional annotation in scRNAseq datasets. Using 8 scRNAseq datasets of immune cell types from human and mouse tissues generated by different sequencing technologies, we show that scSCOPE outperforms other popular methods by automatically identifying marker genes and pathways with the highest consistency across all datasets. We also demonstrate that scSCOPEs gene co-expression and pathway analyses provide in-depth molecular insights into the functionality of identified marker genes. We anticipate that scSCOPE will greatly improve cell type/state annotation and accelerate the design of experimental validation and functional investigations on cell heterogeneity.

bioinformatics↗

bioRxiv2024

Glycine max polygalacturonase inhibiting protein 11 (GmPGIP11) functions in the root to suppress Heterodera glycines parasitism

Pathogen-secreted polygalacturonases (PGs) alter plant cell wall structure by cleaving the - (1[->]4) linkages between D-galacturonic acid residues in homogalacturonan (HG), macerating the cell wall, facilitating infection. Plant PG inhibiting proteins (PGIPs) disengage pathogen PGs, impairing infection. The soybean cyst nematode, Heterodera glycines, obligate root parasite produces secretions, generating a multinucleate nurse cell called a syncytium, a byproduct of the merged cytoplasm of 200-250 root cells, occurring through cell wall maceration. The common cytoplasmic pool, surrounded by an intact plasma membrane, provides a source from which H. glycines derives nourishment but without killing the parasitized cell during a susceptible reaction. The syncytium is also the site of a naturally-occurring defense response that happens in specific G. max genotypes. Transcriptomic analyses of RNA isolated from the syncytium undergoing the process of defense have identified that one of the 11 G. max PGIPs, GmPGIP11, is expressed during defense. Functional transgenic analyses show roots undergoing GmPGIP11 overexpression (OE) experience an increase in its relative transcript abundance (RTA) as compared to the ribosomal protein 21 (GmRPS21) control, leading to a decrease in H. glycines parasitism as compared to the overexpression control. The GmPGIP11 undergoing RNAi experiences a decrease in its RTA as compared to the GmRPS21 control with transgenic roots experiencing an increase in H. glycines parasitism as compared to the RNAi control. Pathogen associated molecular pattern (PAMP) triggered immunity (PTI) and effector triggered immunity (ETI) components are shown to influence GmPGIP11 expression while numerous agricultural crops are shown to have homologs.

plant biology↗

bioRxiv2024

The Diversified Astrocyte Developmental Programs are Modulated by Primary Ciliary Signaling

Astrocyte diversity is greatly influenced by local environmental modulation. Here, we report that the vast majority of brain astrocytes across the entire brain possess a singular primary cilium, a specialized signaling antenna localized to cell soma. Comparative single-cell transcriptomics reveals that primary cilia mediate canonical Shh signaling to modulate astrocyte subtype-specific core features in synaptic regulation, intracellular transport, energy and metabolism. Independent of canonical Shh signaling, primary cilia are important regulators for astrocyte morphology and intracellular signaling balance. Dendritic spine analysis and transcriptomics reveal that perturbation of astrocytic cilia leads to disruption of neuronal development and global intercellular connectomes in the brain. Ultimately, mice with primary ciliary deficient astrocytes show behavioral deficits in sensorimotor function, sociability, learning and memory. Our results uncover a critical role for primary cilia in transmitting local cues that drive the region-specific diversification of astrocytes within the developing brain.

neuroscience↗

bioRxiv2024

CELL CYCLE STATE PREDICTION USING GRAPH NEURAL NETWORKS

Mitosis is a crucial process ensuring the faithful transmission of the genetic information stored in the cell nucleus. Aberrations in this intricate process pose a significant threat to an organisms health, leading to conditions like cancer and various diseases. Hence, the study of mitosis holds paramount importance. Recent investigations have involved manual and semiautomated analyses of time-lapse microscopy images to understand mitosis better. This paper introduces an approach for predicting mitosis stages, employing a Convolutional Neural Network (CNN) as the initial feature extractor, followed by a Graph Neural Network (GNN) for predicting cell cycle states. A distinctive timestamp is incorporated into the feature vectors, treating this information as a graph to leverage internal interactions for predicting the subsequent cell state. To assess performance, experiments were conducted on three datasets, demonstrating that our method exhibits comparable efficacy to state-of-the-art techniques.

cell biology↗

bioRxiv2023

WASP facilitates tumor mechanosensitivity in T lymphocytes

Cytotoxic T lymphocytes (CTLs) carry out immunosurveillance by scanning target cells of diverse physical properties for the presence of antigens. While the recognition of cognate antigen by the T cell receptor is the primary signal for CTL activation, it has become increasingly clear that the mechanical stiffness of target cells plays an important role in antigen-triggered T cell responses. However, the molecular machinery within CTLs that transduces the mechanical information of tumor cells remains unclear. We find that CTLs mechanosensitive ability requires the activity of the actin-organizing protein Wiskott-Aldrich Syndrome Protein (WASP). WASP activation is modulated by the mechanical properties of antigen-presenting contexts across a wide range of target cell stiffnesses and activated WASP then mediates mechanosensitive activation of early TCR signaling markers in the CTL. Our results provide a molecular link between antigen mechanosensing and CTL immune response and suggest that CTL-intrinsic cytoskeletal organizing principles enable the processing of mechanical information from diverse target cells.

immunology↗

bioRxiv2023

sciMET-cap: High-throughput single-cell methylation analysis with a reduced sequencing burden

DNA methylation is a key component of the mammalian epigenome, playing a regulatory role in development, disease, and other processes. Robust, high-throughput single-cell DNA methylation assays are now possible (sciMET); however, the genome-wide nature of DNA methylation results in a high sequencing burden per cell. Here, we leverage target enrichment with sciMET to capture sufficient information per cell for cell type assignment using substantially fewer sequence reads (sciMET-cap). Sufficient off-target coverage further enables the production of near-complete methylomes for individual cell types. We characterize sciMET-cap on human PBMCs and brain (middle frontal gyrus).

genetics↗

bioRxiv2023

Reliable, standardized measurements for cell mechanical properties

Atomic force microscopy (AFM) has become indispensable for studying biological and medical samples. More than two decades of experiments have revealed that cancer cells are softer than healthy cells (for measured cells cultured on stiff substrates). The softness or, more precisely, the larger deformability of cancer cells, primarily independent of cancer types, could be used as a sensitive marker of pathological changes. The wide application of biomechanics in clinics would require designing instruments with specific calibration, data collection, and analysis procedures. For these reasons, such development is, at present, still very limited, hampering the clinical exploitation of mechanical measurements. Here, we propose a standardized operational protocol (SOP), developed within the EU ITN network Phys2BioMed, which allows the detection of the biomechanical properties of living cancer cells regardless of the nanoindentation instruments used (AFMs and other indenters) and the laboratory involved in the research. We standardized the cell cultures, AFM calibration, measurements, and data analysis. This effort resulted in a step-by-step SOP for cell cultures, instrument calibration, measurements, and data analysis, leading to the concordance of the results (Youngs modulus) measured among the six EU laboratories involved. Our results highlight the importance of the SOP in obtaining a reproducible mechanical characterization of cancer cells and paving the way toward exploiting biomechanics for diagnostic purposes in clinics.

biophysics↗

bioRxiv2023

Decoding Root Biogeography: Building Reduced Complexity Functional Rhizosphere Microbial Consortia

The rhizosphere microbiome plays a crucial role in supporting plant productivity and contributes to ecosystem functioning by regulating nutrient cycling, soil integrity, and carbon storage. However, characterizing their functional attributes and microbial relationships remains challenging due to their complex taxonomic and functional compositions. To enable such studies, the development of reduced complexity microbial consortia derived from the rhizosphere microbiome of the natural ecosystem is highly desirable. Designing and assembling reduced complexity consortia that mimic natural communities with consistent, stable, predictable features are highly sought after but is challenging to deliver. Here we present our systematic controlled design towards successful assembly of several such rhizosphere derived reduced complexity consortia. From Brachypodium grown in natural soil under controlled lab conditions, we enriched the root-associated microbes, utilizing carbon compounds prevalent in Brachypodium root exudates. By transferring the enrichments every 3 or 7 days for 9 generations, we developed both fast and slow-growing microbial communities. 16S rRNA amplicon analysis revealed that both inoculum and carbon substrates significantly influence microbial community composition. For example, 1/10 R2A preferentially enriched Amplicon Sequence Variants (ASVs) from slow growing taxa vital to plant including Acidobacteria and Verrucomicrobia. Network analysis revealed that although fast and slow growing microbial consortia have distinct key taxa, the key hubs (keystone taxa) for both belong to genera with plant growth promoting (PGP) traits. This suggests that PGP bacteria might play a central role in controlling the microbial networks among rhizospheric microbiomes. Based on the stability and richness results from different transfers, most carbon substrates lead to microbial consortia with reduced complexity and high stability after a few transfers. The stability tests of the derived microbial consortia also showed high stability, reproducibility, and revivability of the constructed microbial consortia. Our study represents a significant step towards understanding and harnessing the potential of rhizosphere microbiomes, with implications for sustainable agriculture and environmental management.

microbiology↗

bioRxiv2023

Anti-citrullinated protein antibodies with diverse specificities ameliorate collagen antibody-induced arthritis in a time-dependent manner

Anti-citrullinated protein antibodies (ACPAs) are a hallmark of rheumatoid arthritis (RA) and have long been considered to contribute to pathogenesis. In this study, we sequenced the plasmablast antibody repertoires of RA patients and functionally characterized their encoded ACPAs. Recombinantly expressed monoclonal ACPAs bound citrullinated autoantigens, as well as autocitrullinated peptidylarginine deiminase 4 (PAD4). Using the collagen antibody induced arthritis (CAIA) mouse model, we demonstrated that the recombinant ACPAs significantly reduced paw thickness and arthritis severity as compared to isotype-matched control antibodies. Treatment with recombinant ACPAs also significantly reduced bone erosions, synovitis, and cartilage damage in histologic analysis of paws. This amelioration was observed for all the ACPAs tested and was independent of citrullinated antigen specificities. Furthermore, disease amelioration was more prominent when ACPAs were injected at earlier stages of CAIA than at later phases of the model, implying that ACPAs anti-inflammatory effects were more preventative than therapeutic. This study highlights a potential protective role for ACPAs in RA.

immunology↗