Biology subjects

Islam, M. M.

Publications and source records attributed to Islam, M. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Model-driven characterization of functional diversity of Pseudomonas aeruginosa clinical isolates with broadly representative phenotypes

Pseudomonas aeruginosa is a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape of P. aeruginosa clinical isolates. To better understand the metabolic repertoire of P. aeruginosa in infection, we deeply profiled a representative set from a library of 971 clinical P. aeruginosa isolates with corresponding patient metadata and bacterial phenotypes. The genotypic clustering based on whole-genome sequencing of the isolates, multi-locus sequence types, and the phenotypic clustering generated from a multi-parametric analysis were compared to each other to assess the genotype-phenotype correlation. Genome-scale metabolic network reconstructions were developed for each isolate through amendments to an existing PA14 network reconstruction. These network reconstructions show diverse metabolic functionalities and enhance the collective P. aeruginosa pangenome metabolic repertoire. Characterizing this rich set of clinical P. aeruginosa isolates allows for a deeper understanding of the genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences during infection. Impact statementPseudomonas aeruginosa is a leading cause of infections in immunocompromised individuals and in healthcare settings. The treatment of these infections is complicated by the presence of a variety of virulence mechanisms and metabolic uniqueness among clinically relevant strains. This study is an attempt to understand the relationships between isolate phenotypic diversity and the functional metabolic landscape within a representative group of P. aeruginosa clinical isolates. Characterizing this rich set of clinical P. aeruginosa isolates allows for a deeper understanding of genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences in infection.

systems biology↗

bioRxiv2023

The International Weed Genomics Consortium: Community Resources for Weed Genomics Research

The International Weed Genomics Consortium is a collaborative group of researchers focused on developing genomic resources for the study of weedy plants. Weeds are attractive systems for basic and applied research due to their impacts on agricultural systems and capacity to swiftly adapt in response to anthropogenic selection pressures. Our goal is to use genomic information to develop sustainable and effective weed control methods and to provide insights about biotic and abiotic stress tolerance to assist crop breeding. Here, we outline resources under development by the consortium and highlight areas of research that will be impacted by these enabling resources.

genomics↗

bioRxiv2023

Protein engineering, production, reconstitution in lipid nanoparticles, and initial characterization of the Mycobacterium tuberculosis EfpA drug exporter

Mycobacterium tuberculosis (Mtb) drug exporters contribute an efficient mechanism for drug resistance. Therefore, understanding the structure-function relationship in these proteins is important. We focused on the Mtb EfpA efflux pump, which belongs to the major facilitator superfamily (MSF) and transports anti-tuberculosis drugs outside the bacterial cell. Here, we report on our advancements in producing and characterization of this protein. We engineered a construct of apolipoprotein A-I (apoAI) fused to the N-terminus of EfpA (apoAI-EfpA) and cloned it in an E. coli expression vector. This fusion construct was found in a membrane-bound form, unlike the deposited in inclusion bodies EfpA without apoAI. We purified the apoAI-EfpA in detergent to a sufficient degree and reconstituted it in DOPC/DOPS lipids. We found that upon reconstitution in lipid, the apoAI-EfpA forms discoidal protein-lipid nanostructures with a diameter of about 20 nm, resembling nanodiscs. We further detected apoAI-EfpA oligomers in {beta}-DDM and lipid. To the best of our knowledge, this is the first complete protocol on the expression, purification, and lipid reconstitution of the Mtb EfpA transported. AlphaFold2 also predicted EfpA oligomers and further bioinformatic analysis confirmed the earlier proposed 14-transmembrane helices of the Mtb EfpA. We also found very high identity, >80%, among the EfpA-s of diverse mycobacterial species. Outside of mycobacteria, EfpA has no close homologues with only low identity with the QacA family of transporters. These findings possibly indicate high specificity of EfpA mechanisms. Our developments provide a foundation for more comprehensive in vitro studies on the EfpA exporter.

biochemistry↗

bioRxiv2023

HIV-1 Vpu protein forms stable oligomers in aqueous solution via its transmembrane domain self-association

We report our findings on the assembly of the HIV-1 protein Vpu into soluble oligomers. Vpu is a key to HIV-1 protein. It has been considered exclusively a single-pass membrane protein. However, we revealed that this protein forms stable oligomers in aqueous solution, which is an interesting and rather unique observation, as the number of proteins transitioning between soluble and membrane embedded states is limited. Therefore, we undertook a study to characterize these oligomers by utilizing protein engineering, size exclusion chromatography, cryoEM and electron paramagnetic resonance (EPR) spectroscopy. We found that Vpu oligomerizes via its N-terminal transmembrane domain (TM). CryoEM analyses suggest that the oligomeric state most likely is a hexamer or hexamer-to-heptamer equilibrium. Both cryoEM and EPR suggest that, within the oligomer, the distant C-terminal region of Vpu is highly flexible. To the best of our knowledge, this is the first comprehensive study on soluble Vpu. We propose that these oligomers are stabilized via possibly hydrophobic interactions between Vpu TMs. Our findings contribute valuable information about this protein properties and about protein supramolecular complexes formation. The acquired knowledge could be further used in protein engineering, and could also help to uncover possible physiological function of these Vpu oligomers.

biophysics↗

bioRxiv2023

DNA Repair Function Scores for 2172 Variants in the BRCA1 Amino-Terminus

Single nucleotide variants are the most frequent type of sequence changes detected in the genome and these are frequently variants of uncertain significance (VUS). VUS are changes in DNA for which disease risk association is unknown. Thus, methods that classify the functional impact of a VUS can be used as evidence for variant interpretation. In the case of the breast and ovarian cancer specific tumor suppressor protein, BRCA1, pathogenic missense variants frequently score as loss of function in an assay for homology-directed repair (HDR) of DNA double-strand breaks. We previously published functional results using a multiplexed assay for 1056 amino acid substitutions residues 2-192 in the amino terminus of BRCA1. In this study, we have re-assessed the data from this multiplexed assay using an improved analysis pipeline. These new analysis methods yield functional scores for more variants in the first 192 amino acids of BRCA1, plus we report new results for BRCA1 amino acid residues 193-302. We now present the functional classification of 2172 BRCA1 variants in BRCA1 residues 2-302 using the multiplexed HDR assay. Comparison of the functional determinations of the missense variants with clinically known benign or pathogenic variants indicated 93% sensitivity and 100% specificity for this assay. The results from BRCA1 variants tested in this assay are a resource for clinical geneticists for evidence to evaluate VUS in BRCA1. AUTHOR SUMMARYMost missense substitutions in BRCA1 are variants of unknown significance (VUS), and individuals with a VUS in BRCA1 cannot know from genetic information alone whether this variant predisposes to breast or ovarian cancer. We apply a multiplexed functional assay for homology directed repair of DNA double strand breaks to assess variant impact on this important BRCA1 protein function. We analyzed 2172 variants in the amino-terminus of BRCA1 and demonstrate that variants that are known as pathogenic have a loss of function in the DNA repair assay. Conversely, variants that are known to be benign are functionally normal in the multiplexed assay. We suggest that these functional determinations of BRCA1 variants can be used to augment the information that clinical cancer geneticists provide to patients who have a VUS in BRCA1.

cancer biology↗

bioRxiv2023

MOGAT: An Improved Multi-Omics Integration Framework Using Graph Attention Networks

Integration of multi-omics data holds great promise for understanding the complex biology of diseases, particularly Alzheimers, Parkinsons, and cancer. However, the integration is challenging due to the high dimensionality and complexity of the data. Traditional machine learning methods are not well-suited for handling the complex relationships between different types of omics data. Many models were proposed that utilize graph-based learning models to extract hidden representations and network structures from different omics data to enhance cancer prediction, patient categorization, etc. The existing graph neural network-based (GNN-based) multi-omics approaches for cancer subtype prediction have three shortcomings: (a) Do not consider all types of omics data, (b) Fail to determine the relative significance of the neighboring nodes (in this case, samples or patients) when it comes to downstream analyses, such as subtype classification, patient stratification, etc., and (c) Use the same approach for generating initial graphs for different omics data. To overcome these shortcomings, we present MOGAT, a novel multi-omics integration approach, leveraging a graph attention network (GAT) model that incorporates graph-based learning with an attention mechanism. MOGAT utilizes a multi-head attention mechanism that can more efficiently extract information for a specific sample by assigning unique attention coefficients to its neighboring samples. To evaluate the performance of MOGAT, we explored its capability via a case study of predicting breast cancer subtypes. Our results showed that MOGAT performs better than the state-of-the-art multi-omics integration approaches.

bioinformatics↗

bioRxiv2022

Oligomeric polymorphism of HIV-1 Vpu protein in lipid environment and in solution

The HIV-1 encoded protein Vpu forms an oligomeric ion channel/pore in membranes and interacts with multiple host proteins to support virus lifecycle. However, Vpu molecular mechanisms are currently not well understood. The structures of full-length Vpu in its monomeric and oligomeric forms are unknown, although both the monomer and oligomer are deemed important. Here, we report on the diversity of Vpu oligomeric structures and how the environment affects the Vpu oligomer formation. We produced a uniquely designed MBP-Vpu chimera protein in E. coli in soluble form. We subjected this protein to analytical size exclusion chromatography (SEC) and negative staining electron microscopy (nsEM). Strikingly, we found that MBP-Vpu forms stable oligomers in solution, presumably driven by Vpu transmembrane domain self-association. Our coarse modeling suggests that these oligomers are pentamers, in agreement with the pentameric membrane-bound Vpu. To the best of our knowledge, this is the first observation of Vpu self-association out of lipid membrane environment. We further found that MBP-Vpu oligomer stability decreases when the protein was reconstituted in lipid membrane mimetics, such as {beta}-DDM, and mixtures of lyso PC/PG or DHPC/DHPG--In these cases significant oligomer heterogeneity was observed with oligomeric order lesser than that of MBP-Vpu oligomer in solution, but larger oligomers were observed as well. Importantly, we found that in lyso PC/PG, above certain protein concentration, MBP-Vpu forms linear array-like structures, which is also novel. Thus, our studies provide unique information about Vpu protein quaternary organization by capturing multiple Vpu oligomeric structures, which we believe are physiologically relevant.

biochemistry↗

bioRxiv2021

Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling

Pancreatic ductal adenocarcinoma (PDAC) is a major research focus due to its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism efficiently to the environment to which they are exposed, often relying on diverse fuel sources depending on availability. Since traditional experimental techniques appear exhaustive in the search for a viable therapeutic strategy against PDAC, in this study, a highly curated and omics-informed genome-scale metabolic model of PDAC was reconstructed using patient-specific transcriptomic data. From the analysis of the model-predicted metabolic changes, several new metabolic functions were explored as potential therapeutic targets against PDAC in addition to the already known metabolic hallmarks of pancreatic cancer. Significant downregulation in the peroxisomal fatty acid beta oxidation pathway reactions, flux modulation in the carnitine shuttle system, and upregulation in the reactive oxygen species detoxification pathway reactions were observed. These unique metabolic traits of PDAC were then correlated with potential drug combinations that can be repurposed for targeting genes with poor prognosis in PDAC. Overall, these studies provide a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies. Author summaryPancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, with late diagnosis, early metastasis, insufficient therapy response, and very low survival rates. Due to these challenges associated with the diagnosis and treatment of PDAC, it has been a research area of interest. With the goal of understanding the metabolic reprogramming in proliferating PDAC cells, we reconstructed healthy and PDAC models by incorporating patient transcriptomic data into a genome-scale global human metabolic model. Comparing the metabolic flux space for the reactions in the two context-specific models, we identified significantly divergent pathways in PDAC. These results allowed us to further investigate growth-limiting genes in PDAC and identify potential drug combinations that can be repositioned for treatment of PDAC.

systems biology↗

bioRxiv2021

Multiparametric assessment of cellular lipid metabolism in hypercholesterolemia

Systematic insight into cellular dysfunctions can improve understanding of disease etiology, risk assessment and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validated this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrated lipid storage data into a novel readout, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlated positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explained hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking from a few mls of blood and is applicable to dissect metabolic disorders, such as hypercholesterolemia. MotivationWe have limited information on how cellular lipid uptake and processing differ between individuals and influence the development of metabolic diseases, such as hypercholesterolemia. Available assays are labor intensive, require skilled personnel and are difficult to scale to higher throughput, making it challenging to obtain systematic functional cell-based data from individuals. To overcome this problem, we established a scalable automated analysis pipeline enabling reliable quantification of multiple cellular readouts, including lipid uptake, storage and mobilization, from different white blood cell populations. This approach provides new personalized insights into the cellular basis of hypercholesterolemia and obesity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/440471v4_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@9222c1org.highwire.dtl.DTLVardef@27e289org.highwire.dtl.DTLVardef@89ba82org.highwire.dtl.DTLVardef@33c9cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

Better expression profile of CD8 and CD4 gene in uterus of pregnant ewe in comparison to non-pregnant - a novel report

CD8 and CD4 T cells play a central role in the immune response to viruses and intracellular pathogens as well as functions for the maintenance of both the mother and fetus. The present study was conducted to explore the differential gene expression profile for CD8 and CD4 present in the uterus with reference to the gravid and non-gravid Garole sheep and confirmation through immuno histochemical studies. Better CD8 and CD4 gene expression was observed in the mid uterus of pregnant ewes compared to that of non-pregnant ewes, where CD8 expression was better to that of CD4. Gene expression profiling of CD8 and CD4 are reported here for the first time in sheep. CD8 and CD4 expression may be regarded as the useful factor for maintenance of pregnancy. The current observations demonstrate that during pregnancy in ewe the immune system may respond to changes in the maternal environment to maintain the size and function of the CD8 and CD4 T-cell compartment. CD8 and CD4 expression may be employed as marker for pregnancy detection in sheep, which remains always a challenge for sheep breeders.

immunology↗

bioRxiv2020

Honeyweed (Leonurus sibiricus) and Buckwheat (Fagopyrum esculentum) supplemented diet improve growth performance, lipid profile and hematological values of broiler chicks

The study was conducted to investigate the combined effects of honeyweed (HW) and buckwheat (BW) supplemented diets on the growth, feed intake, serum lipid profile and blood parameters in broiler chicks. One hundred fifty (150) day old chicks (Cobb-500) were divided into five groups viz. T1 (Commercial control, CC), T2 (FF+10% BW), T3 (FF+10% BW +5% (w/v) HW powder), T4 (FF+10% BW +10% (w/v) HW powder), T5 (FF+10% BW +15% (w/v) HW powder) in complete randomized design with five (5) replications, each of which contain six (6) birds. The CC feed and the FF with HW and BW supplemented diet fed on broiler for 30 days. At the end of the study, the body weight gain, FCR and mortality rate were calculated. It was found that T3 (FF+10% BW +5% (w/v) HW powder) diet significantly (p <0.05) showed the good FCR, mortality rate and body weight gain. Interestingly, T3 decreased the serum cholesterol, triglycerides (TG), low density lipoprotein (LDL), increased high density lipoprotein (HDL) and improves blood parameters significantly (p < 0.05). Our results suggested that this newly formulated feed T3 (FF+10% BW +5% (w/v) HW powder) could be considered as an alternative natural feed additive to hazardous synthetic antibiotics.Competing Interest StatementThe authors have declared no competing interest.View Full Text

animal behavior and cognition↗

bioRxiv2020

A systematic mutational analysis identifies a 5-residue proline tag that enhances the in vivo immunogenicity of a non-immunogenic model protein 240 folds

Small proteins are generally non-immunogenic, which can be a major hurdle in developing protein and peptide vaccines or producing antibodies for biopharmaceutical usage. For improving a proteins immunogenicity, we previously proposed to use short Solubility Controlling Peptide (SCP) tags that oligomerize proteins into soluble aggregates. Here, we systematically analyzed the effect of SCP-tags that do not induce oligomerization on the immunogenicity of a small, non-immunogenic, model protein, Bovine Pancreatic Trypsin Inhibitor (BPTI-19A; 6 kDa). We assessed the effect of the following ten SCP-tags: Six tags made of five consecutive Arg, Lys, His, Asp, Asn, Pro; one made of seven Pro; two tags made of consecutive Arg-lle and Asn-Ile, all attached at the C-terminus of BPTI-19A; and a 5-proline tag attached at the N-terminus. Circular dichroism, fluorescence, dynamic light scattering measurements, and analytical ultra-centrifugation indicated that the addition of the SCP-tags did not change the secondary structure content nor the tertiary structures of the protein nor its monomeric state. On the other hand, the C-terminus 5-proline (C5P) tag unexpectedly increased the immunogenicity (IgG level) of BPTI-19A by up to 240 fold as assessed by ELISA. Additionally, the 5-arginine tag (C5R) increased the titer by up to 73 fold. The titer increase lasted for several weeks, and the effect was cumulative to that of the Freunds adjuvant, which is commonly used to boost a proteins immunogenicity. Altogether, SCP-tags that do not oligomerize proteins substantially increased the immunogenicity of a non-immunogenic protein, suggesting that the 5-proline and the 5-arginine SCP-tags may provide a novel tool for facilitating the production of antibodies or improving the effectiveness of protein-based vaccines.

immunology↗

bioRxiv2020

Systematic mutational analysis of epitope-grafted ED3's immunogenicity reveals a DENV3-DENV4 bi-serospecific ED3 mutant

Dengue viruses are classified into four serotypes (DENV1[~]4), and the severe forms of dengue disease, the dengue hemorrhagic fever and shock syndrome, are caused by sero-cross-reacting antibodies. However, the residue determinants of the serospecificity and sero-cross-reactivity are yet to be identified. Here, we report an epitope grafting mutational analysis of the serospecificity and cross-serospecificity of the envelope protein domain 3 (ED3; 107 residues, [~]11.6kDa), which contains two major putative epitopes of DENVs. To this end, we constructed ED3 from DENV3 (3ED3) and DENV4 (4ED3), and six epitope-grafted variants, where we transferred epitope 1 (L304I, K305D, V309M, and S310A) and/or epitope 2 (D383N, K384S, K387T, and N389H) of 4ED3 onto 3ED3 and vice versa. Mice immunization using 3ED3 and 4ED3 generated serotype-specific antisera, as expected. Similarly, most epitope-grafted ED3s produced antisera serospecific to the template ED3 with little or no cross-recognition of ED3 of the serotype from which the epitopes were taken. This result indicated that a mere grafting of the epitope was not sufficient to transfer serospecificity, contrary to our expectations. However, one epitope grafted ED3 mutant, where epitope 1 of 3ED3 was grafted onto 4ED3 (4ED3epi1), generated antisera that was serospecific to both 4ED3 and 3ED3. The 4ED3epi1 is thus a chimeric ED3 that produces antisera possessing serospecificity to both 3ED3 and 4ED3. The 4ED3epi1 provides a unique tool for analyzing serospecificity and cross-reactivity in dengue, and we hope it will serve as a template for trivalent and eventually tetravalent antisera.

immunology↗

bioRxiv2020

Phylogenomic terraces: presence and implication in species tree estimation from gene trees

Species tree estimation from multi-locus dataset is extremely challenging, especially in the presence of gene tree heterogeneity across the genome due to incomplete lineage sorting (ILS). Summary methods have been developed which estimate gene trees and then combine the gene trees to estimate a species tree by optimizing various optimization scores. In this study, we have formalized the concept of "phylogenomic terraces" in the species tree space, where multiple species trees with distinct topologies may have exactly the same optimization score (quartet score, extra lineage score, etc.) with respect to a collection of gene trees. We investigated the presence and implication of terraces in species tree estimation from multi-locus data by taking ILS into account. We analyzed two of the most popular ILS-aware optimization criteria: maximize quartet consistency (MQC) and minimize deep coalescence (MDC). Methods based on MQC are provably statistically consistent, whereas MDC is not a consistent criterion for species tree estimation. Our experiments, on a collection of dataset simulated under ILS, indicate that MDC-based methods may achieve competitive or identical quartet consistency score as MQC but could be significantly worse than MQC in terms of tree accuracy - demonstrating the presence and affect of phylogenomic terraces. This is the first known study that formalizes the concept of phylogenomic terraces in the context of species tree estimation from multi-locus data, and reports the presence and implications of terraces in species tree estimation under ILS.

bioinformatics↗

bioRxiv2020

Investigation of microbial community interactions between lake Washington methanotrophs using genome-scale metabolic modeling

BackgroundThe role of methane in global warming has become paramount to the environment and the human society, especially in the past few decades. Methane cycling microbial communities play an important role in the global methane cycle, which is why the characterization of these communities is critical to understand and manipulate their behavior. Methanotrophs are a major player in these communities and are able to oxidize methane as their primary carbon source. ResultsLake Washington is a freshwater lake characterized by a methane-oxygen countergradient that contains a methane cycling microbial community. The major microbial members include methanotrophs such as Methylobacter Tundripaludum 21/22 and Methylomonas sp. LW13. In this work, these methanotrophs are studied via developing highly curated genome-scale metabolic models. Each model was then integrated to form a community model with a multi-level optimization framework. The metabolic interactions for the community were also characterized. While both organisms are competitors for methane, Methylobacter was found to display altruistic behavior in consuming formaldehyde produced by Methylomonas that inhibits its growth. The community was next tested under carbon, oxygen, and nitrogen limited conditions to observe the systematic shifts in the internal metabolic pathways and extracellular metabolite exchanges. Each condition showed variable differences within the methane oxidation pathway, serine cycle, pyruvate metabolism, and the TCA cycle as well as the excretion of formaldehyde and carbon di-oxide from the community. Finally, the community model was simulated under fixed ratios of these two members to reflect the opposing behavior of the community in synthetic and natural communities. The simulated community demonstrated a noticeable switch in intracellular carbon metabolism and formaldehyde transfer between community members in natural vs. synthetic condition. ConclusionIn this work, we attempted to reveal the response of a simplified methane recycling microbial community from Lake Washington to varying environments and also provide an insight into the difference of dynamics in natural community and synthetic co-cultures. Overall, this study lays the ground for in silico systems-level studies of freshwater lake ecosystems, which can drive future efforts of understanding, engineering, and modifying these communities for dealing with global warming issues.

systems biology↗

bioRxiv2020

In Silico Identification, Characterization and Diversity Analysis of RNAi Genes and their Associated Regulatory Elements in Sweet Orange (Citrus sinensis L)

RNA interference (RNAi) plays key roles in post-transcriptional and chromatin modification levels as well as regulates various eukaryotic gene expressions which involved in stress responses, development and maintenance of genome integrity during developmental stages. The whole mechanism of RNAi pathway is directly involved with the gene-silencing process by the interaction of Dicer-Like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) gene families. However, the genes of these three RNAi families are largely unknown yet in sweet orange (Citrus sinensis), though it is an economically important fruit plant all over the world. Therefore, a comprehensive investigation for genome-wide identification, characterization and diversity analysis of RNA silencing genes in C. sinensis was conducted and identified 4 CsDCL, 8 CsAGO and 4 CsRDR as RNAi genes. To characterize and validate the predicted genes of RNAi families, various bioinformatics analysis was conducted. Phylogenetic analysis clustered the predicted CsDCLs, CsAGOs and CsRDRs genes into four, six and four subgroups with the relevant genes of Arabidopsis respectively. The domain and motif composition analysis, the gene structure for all three-gene families exhibited almost homogeneity within the same group members while showed significant differences in between groups. The GO enrichment analysis results clearly indicated that the predicted genes have direct involvement into the RNAi process as expected in C. sinensis. Moreover, Cis-regulatory elements and regulatory transcription factor analysis of the reported RNAi genes demonstrated the diverse connection to the huge biological functions and regulatory pathways. The expressed sequence tag (EST) analysis showed that these genes are highly expressed in fruit and leaves which indicate that these reported genes have great involvement in C. sinensis food, flowering and fruit production. The expression analysis of the reported RNAi genes might be more useful to explore the most effective RNAi genes in C. sinensis for further biotechnological application.

genomics↗

bioRxiv2019

Collagen-based scaffolds with infused anti-VEGF release system as potential cornea substitute for high-risk keratoplasty: An in vitro evaluation

Currently the only widely accepted corneal blindness treatment is to replace it by transplantation with human donor cornea. However, increasing shortage of donor corneas as well as high risk of rejection in some corneal diseases remain two major problems, which limit the success of corneal transplantation. Corneal neovascularization is considered as one of the main risk factors of graft failure. Different cell-free biosynthetic scaffolds fabricated from collagens or collagen-like peptides are being tested as donor cornea substitutes (DCS). Here, we report for the first-time composite biosynthetic DCS with integrated sustained release system of anti-VEGF drug, bevacizumab and their in vitro validation. We have tethered gold nanoparticles with bevacizumab and integrated into a collagen-based cell-free hydrogel scaffold. Developed grafts preserved good optical properties and were confirmed not toxic to human corneal epithelial cells. Bevacizumab has been shown to constantly releasing from the DCS up to 3 weeks and preserved its anti-angiogenic properties. These results provide background for further use of infused composite biosynthetic DCS with integrated nanosystem of bevacizumab sustained release in corneal disease accompanied by neovascularisation where conventional corneal transplantation might fail.

bioengineering↗

bioRxiv2019

eMED-DNA: An in silico operating system for clinical medical data storage within the human genome

The propitious developments in molecular biology and next generation sequencing have enabled the possibility for DNA storage technologies. However, the full application and power of our genomic revolution have not been fully utilized in clinical medicine given a lack of transition from research to real world clinical practice. This has identified an increasing need for an operating system which allows for the transition from research to clinical use. We present eMED-DNA, an in silico operating system for archiving and managing all forms of electronic health records (EHRs) within ones own copy of the sequenced genome to aid in the application and integration of genomic medicine within real world clinical practice. We incorporated an efficient and sophisticated in-DNA file management system for the lossless management of EHRs within a genome. This represents the first in silico integrative system which would bring closer the utopian ideal for integrating genotypic data with phenotypic clinical data for future medical practice.

bioinformatics↗