Mol Syst Biol. 2021 Apr;17(4):e10060. doi: 10.15252/msb.202010060.

ABSTRACT

Sample multiplexing facilitates single-cell sequencing by reducing costs, revealing subtle difference between similar samples, and identifying artifacts such as cell doublets. However, universal and cost-effective strategies are rather limited. Here, we reported a concanavalin A-based sample barcoding strategy (CASB), which could be followed by both single-cell mRNA and ATAC (assay for transposase-accessible chromatin) sequencing techniques. The method involves minimal sample processing, thereby preserving intact transcriptomic or epigenomic patterns. We demonstrated its high labeling efficiency, high accuracy in assigning cells/nuclei to samples regardless of cell type and genetic background, and high sensitivity in detecting doublets by three applications: 1) CASB followed by scRNA-seq to track the transcriptomic dynamics of a cancer cell line perturbed by multiple drugs, which revealed compound-specific heterogeneous response; 2) CASB together with both snATAC-seq and scRNA-seq to illustrate the IFN-γ-mediated dynamic changes on epigenome and transcriptome profile, which identified the transcription factor underlying heterogeneous IFN-γ response; and 3) combinatorial indexing by CASB, which demonstrated its high scalability.

PMID:33821571 | DOI:10.15252/msb.202010060

Mol Syst Biol. 2021 Apr;17(4):e10093. doi: 10.15252/msb.202010093.

ABSTRACT

Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, such as Lactococcus lactis. Here, we present a proteome-constrained genome-scale metabolic model of L. lactis (pcLactis) to interpret growth on multiple nutrients. Through integration of proteomics and flux data, in glucose-limited chemostats, the model predicted glucose and arginine uptake as dominant constraints at low growth rates. Indeed, glucose and arginine catabolism were found upregulated in evolved mutants. At high growth rates, pcLactis correctly predicted the observed shutdown of arginine catabolism because limited proteome availability favored lactate for ATP production. Thus, our model-based analysis is able to identify and explain the proteome constraints that limit growth rate in nutrient-rich environments and thus form targets of fitness improvement.

PMID:33821549 | DOI:10.15252/msb.202010093

Nat Genet. 2021 Apr 5. doi: 10.1038/s41588-021-00827-w. Online ahead of print.

ABSTRACT

Evidence from model organisms and clinical genetics suggests coordination between the developing brain and face, but the role of this link in common genetic variation remains unknown. We performed a multivariate genome-wide association study of cortical surface morphology in 19,644 individuals of European ancestry, identifying 472 genomic loci influencing brain shape, of which 76 are also linked to face shape. Shared loci include transcription factors involved in craniofacial development, as well as members of signaling pathways implicated in brain-face cross-talk. Brain shape heritability is equivalently enriched near regulatory regions active in either forebrain organoids or facial progenitors. However, we do not detect significant overlap between shared brain-face genome-wide association study signals and variants affecting behavioral-cognitive traits. These results suggest that early in embryogenesis, the face and brain mutually shape each other through both structural effects and paracrine signaling, but this interplay may not impact later brain development associated with cognitive function.

PMID:33821002 | DOI:10.1038/s41588-021-00827-w

Nat Chem Biol. 2021 Apr 5. doi: 10.1038/s41589-021-00779-6. Online ahead of print.

ABSTRACT

Genetically modified microorganisms (GMMs) can enable a wide range of important applications including environmental sensing and responsive engineered living materials. However, containment of GMMs to prevent environmental escape and satisfy regulatory requirements is a bottleneck for real-world use. While current biochemical strategies restrict unwanted growth of GMMs in the environment, there is a need for deployable physical containment technologies to achieve redundant, multi-layered and robust containment. We developed a hydrogel-based encapsulation system that incorporates a biocompatible multilayer tough shell and an alginate-based core. This deployable physical containment strategy (DEPCOS) allows no detectable GMM escape, bacteria to be protected against environmental insults including antibiotics and low pH, controllable lifespan and easy retrieval of genomically recoded bacteria. To highlight the versatility of DEPCOS, we demonstrated that robustly encapsulated cells can execute useful functions, including performing cell-cell communication with other encapsulated bacteria and sensing heavy metals in water samples from the Charles River.

PMID:33820990 | DOI:10.1038/s41589-021-00779-6

Nat Metab. 2020 Apr;2(4):381. doi: 10.1038/s42255-020-0202-0.

NO ABSTRACT

PMID:33820984 | DOI:10.1038/s42255-020-0202-0

Nat Cell Biol. 2021 Apr 5. doi: 10.1038/s41556-021-00652-7. Online ahead of print.

ABSTRACT

Although high-throughput RNA sequencing (RNA-seq) has greatly advanced small non-coding RNA (sncRNA) discovery, the currently widely used complementary DNA library construction protocol generates biased sequencing results. This is partially due to RNA modifications that interfere with adapter ligation and reverse transcription processes, which prevent the detection of sncRNAs bearing these modifications. Here, we present PANDORA-seq (panoramic RNA display by overcoming RNA modification aborted sequencing), employing a combinatorial enzymatic treatment to remove key RNA modifications that block adapter ligation and reverse transcription. PANDORA-seq identified abundant modified sncRNAs-mostly transfer RNA-derived small RNAs (tsRNAs) and ribosomal RNA-derived small RNAs (rsRNAs)-that were previously undetected, exhibiting tissue-specific expression across mouse brain, liver, spleen and sperm, as well as cell-specific expression across embryonic stem cells (ESCs) and HeLa cells. Using PANDORA-seq, we revealed unprecedented landscapes of microRNA, tsRNA and rsRNA dynamics during the generation of induced pluripotent stem cells. Importantly, tsRNAs and rsRNAs that are downregulated during somatic cell reprogramming impact cellular translation in ESCs, suggesting a role in lineage differentiation.

PMID:33820973 | DOI:10.1038/s41556-021-00652-7

Nat Ecol Evol. 2021 Apr 5. doi: 10.1038/s41559-021-01435-x. Online ahead of print.

ABSTRACT

Across diverse taxa, selfing species have evolved independently from outcrossing species thousands of times. The transition from outcrossing to selfing decreases the effective population size, effective recombination rate and heterozygosity within a species. These changes lead to a reduction in genetic diversity, and therefore adaptive potential, by intensifying the effects of random genetic drift and linked selection. Within the nematode genus Caenorhabditis, selfing has evolved at least three times, and all three species, including the model organism Caenorhabditis elegans, show substantially reduced genetic diversity relative to outcrossing species. Selfing and outcrossing Caenorhabditis species are often found in the same niches, but we still do not know how selfing species with limited genetic diversity can adapt to these environments. Here, we examine the whole-genome sequences from 609 wild C. elegans strains isolated worldwide and show that genetic variation is concentrated in punctuated hyper-divergent regions that cover 20% of the C. elegans reference genome. These regions are enriched in environmental response genes that mediate sensory perception, pathogen response and xenobiotic stress response. Population genomic evidence suggests that genetic diversity in these regions has been maintained by long-term balancing selection. Using long-read genome assemblies for 15 wild strains, we show that hyper-divergent haplotypes contain unique sets of genes and show levels of divergence comparable to levels found between Caenorhabditis species that diverged millions of years ago. These results provide an example of how species can avoid the evolutionary dead end associated with selfing.

PMID:33820969 | DOI:10.1038/s41559-021-01435-x

Transl Psychiatry. 2021 Apr 6;11(1):193. doi: 10.1038/s41398-021-01302-0.

ABSTRACT

Major depressive disorder (MDD) is associated with premature mortality and is an independent risk factor for a broad range of diseases, especially those associated with aging, such as cardiovascular disease, diabetes, and Alzheimer's disease. However, the pathophysiology underlying increased rates of somatic disease in MDD remains unknown. It has been proposed that MDD represents a state of accelerated cellular aging, and several measures of cellular aging have been developed in recent years. Among such metrics, estimators of biological age based on predictable age-related patterns of DNA methylation (DNAm), so-called 'epigenetic clocks', have shown particular promise for their ability to capture accelerated aging in psychiatric disease. The recently developed DNAm metric known as 'GrimAge' is unique in that it was trained on time-to-death data and has outperformed its predecessors in predicting both morbidity and mortality. Yet, GrimAge has not been investigated in MDD. Here we measured GrimAge in 49 somatically healthy unmedicated individuals with MDD and 60 age-matched healthy controls. We found that individuals with MDD exhibited significantly greater GrimAge relative to their chronological age ('AgeAccelGrim') compared to healthy controls (p = 0.001), with a median of 2 years of excess cellular aging. This difference remained significant after controlling for sex, current smoking status, and body-mass index (p = 0.015). These findings are consistent with prior suggestions of accelerated cellular aging in MDD, but are the first to demonstrate this with an epigenetic metric predictive of premature mortality.

PMID:33820909 | DOI:10.1038/s41398-021-01302-0

Crit Rev Biochem Mol Biol. 2021 Apr 5:1-20. doi: 10.1080/10409238.2021.1908953. Online ahead of print.

ABSTRACT

Found in virtually every organism, glycans are essential molecules that play important roles in almost every aspect of biology. The composition of glycome, the repertoire of glycans in an organism or a biological sample, is often found altered in many diseases, including cancer, infectious diseases, metabolic and developmental disorders. Understanding how glycosylation and glycomic changes enriches our knowledge of the mechanisms of disease progression and sheds light on the development of novel therapeutics. However, the inherent diversity of glycan structures imposes challenges on the experimental characterization of glycomes. Advances in high-throughput glycomic technologies enable glycomic analysis in a rapid and comprehensive manner. In this review, we discuss the analytical methods currently used in high-throughput glycomics, including mass spectrometry, liquid chromatography and lectin microarray. Concomitant with the technical advances is the integration of glycomics into systems biology in the recent years. Herein we elaborate on some representative works from this recent trend to underline the important role of glycomics in such integrated approaches to disease.

PMID:33820453 | DOI:10.1080/10409238.2021.1908953

Genomics. 2021 Apr 2:S0888-7543(21)00122-1. doi: 10.1016/j.ygeno.2021.03.030. Online ahead of print.

ABSTRACT

The perennial ornamental peanut Arachis glabrata represents one of the most adaptable wild Arachis species. This study used PacBio combined with BGISEQ-500 RNA-seq technology to study the transcriptome and gene expression dynamics of A. glabrata. Of the total 109,747 unique transcripts obtained, >90,566 transcripts showed significant homology to known proteins and contained the complete coding sequence (CDS). RNA-seq revealed that 1229, 1039, 1671, 3923, 1521 and 1799 transcripts expressed specifically in the root, stem, leaf, flower, peg and pod, respectively. We also identified thousands of differentially expressed transcripts in response to drought, salt, cold and leaf spot disease. Furthermore, we identified 30 polyphenol oxidase encoding genes associated with the quality of forage, making A. glabrata suitable as a forage crop. Our findings presented the first transcriptome study of A. glabrata which will facilitate genetic and genomics studies and lays the groundwork for a deeper understanding of the A. glabrata genome.

PMID:33819563 | DOI:10.1016/j.ygeno.2021.03.030

New Phytol. 2021 Apr 5. doi: 10.1111/nph.17380. Online ahead of print.

ABSTRACT

Rooted in place, plants are faced with the challenge of responding to unfavourable conditions on-site. One such condition, heat stress, contributes massively to crop losses globally. With heatwaves predicted to increase, it is of vital importance to generate crops tolerant to not only one, but several other abiotic stresses (e.g. drought stress, salinity stress), which will ensure that global food security is protected. A better understanding of the molecular mechanisms that underlie the temperature stress response in pollen will be a significant step towards developing effective breeding strategies for high and stable production in crop plants. While most studies have focused on the vegetative phase of plant growth to understand heat stress tolerance, it is the reproductive phase that requires more attention, being more sensitive to elevated temperatures. Every phase of reproductive development is affected by environmental challenges, including pollen and ovule development, pollen tube growth, male-female cross-talk, fertilization, and embryo development. In this review we summarize how pollen is affected by heat stress and the molecular mechanisms employed during the stress period, as revealed by classical and -omics experiments.

PMID:33818773 | DOI:10.1111/nph.17380

Mol Oncol. 2021 Apr 4. doi: 10.1002/1878-0261.12960. Online ahead of print.

ABSTRACT

Somatic mutations in the KRAS oncogene are associated with poor outcomes in locally advanced rectal cancer but the underlying biologic mechanisms are not fully understood. We profiled mRNA in 76 locally advanced rectal adenocarcinomas from patients that were enrolled in a prospective clinical trial and investigated differences in gene expression between KRAS-mutant (KRAS-mt) and KRAS-wild-type (KRAS-wt) patients. We found that KRAS-mt tumors display lower expression of genes related to the tumor stroma and remodeling of the extracellular matrix. We validated our findings using samples from The Cancer Genome Atlas (TCGA) data and also by performing immunohistochemistry (IHC) and immunofluorescence (IF) in orthogonal cohorts. Using in vitro and in vivo models, we show that oncogenic KRAS signaling within the epithelial cancer cells modulates the activity of the surrounding fibroblasts in the tumor microenvironment.

PMID:33817986 | DOI:10.1002/1878-0261.12960

Mol Ecol. 2021 Apr 4. doi: 10.1111/mec.15912. Online ahead of print.

ABSTRACT

The Amazonian floodplain forests are dynamic ecosystems of great importance for the regional hydrological and biogeochemical cycles and function as a significant CH4 source contributing to the global carbon balance. Unique geochemical factors may drive the microbial community composition and, consequently, affect CH4 emissions across floodplain areas. Here we report the in situ composition of CH4 cycling microbial communities in Amazonian floodplain sediments. We asked how abiotic factors may affect the microbial community composition and, more specifically, CH4 cycling groups. We collected sediment samples during wet and dry seasons from three different types of floodplain forests, along with upland forest soil samples, from the Eastern Amazon, Brazil. We used high-resolution sequencing of archaeal and bacterial 16S rRNA genes combined with real-time PCR to quantify Archaea and Bacteria, as well as key functional genes indicative of the presence of methanogenic (mcrA) and methanotrophic (pmoA) microorganisms. Methanogens were found to be present in high abundance in floodplain sediments, and they seem to resist the dramatic environmental changes between flooded and non-flooded conditions. Methanotrophs known to use different pathways to oxidise CH4 were detected, including anaerobic archaeal and bacterial taxa, indicating that a wide metabolic diversity may be harboured in this highly variable environment. The floodplain environmental variability, which is affected by the river origin, drives not only the sediment chemistry but also the composition of the microbial communities. These environmental changes seem also to affect the pools of methanotrophs occupying distinct niches. Understanding these shifts in the methanotrophic communities could improve our comprehension of the CH4 emissions in the region.

PMID:33817881 | DOI:10.1111/mec.15912

Brain Behav Immun Health. 2021 Jul;14:100243. doi: 10.1016/j.bbih.2021.100243. Epub 2021 Mar 26.

ABSTRACT

BACKGROUND: IFITM3 is a viral restriction protein that enables sequestration of viral particles and subsequent trafficking to lysosomes. Recently, IFITM3 upregulation was found to induce gamma - secretase activity and the production of amyloid beta. The purpose of this study was to determine whether dysregulation of IFITM3-dependent pathways was present in neurons and peripheral immune cells donated by AD patients. As a secondary aim, we sought to determine whether these perturbations could be induced by viruses, including SARS-CoV-2.

METHODS: Gene set enrichment analyses (GSEA) previously performed on publicly available transcriptomic data from tissues donated by AD patients were screened for enriched pathways containing IFITM3. Subsequently, signature containing IFITM3, derived from entorhinal cortex (EC) neurons containing neurofibrillary tangles (NFT) was screened for overlap with curated, publicly available, viral infection-induced gene signatures (including SARS-CoV-2).

RESULTS: GSEA determined that IFITM3 gene networks are significantly enriched both in CNS sites (entorhinal and hippocampal cortices) and in peripheral blood mononuclear cells (PBMCs) donated by AD patients. Overlap screening revealed that IFITM3 signatures are induced by several viruses, including SARS-CoV, MERS-CoV, SARS-CoV-2 and HIV-1 (adjusted p-value <0.001; Enrichr Database).

DISCUSSION: A data-driven analysis of AD tissues revealed IFITM3 gene signatures both in the CNS and in peripheral immune cells. GSEA revealed that an IFITM3 derived gene signature extracted from EC/NFT neurons overlapped with those extracted from publicly available viral infection datasets, including SARS-CoV-2. Our results are in line with currently emerging evidence on IFITM3's role in AD, and SARS-CoV-2's potential contribution in the setting of an expanded antimicrobial protection hypothesis.

PMID:33817671 | PMC:PMC7997139 | DOI:10.1016/j.bbih.2021.100243

Open Life Sci. 2020 Dec 21;15(1):923-938. doi: 10.1515/biol-2020-0095. eCollection 2020.

ABSTRACT

Variation in atmospheric carbon dioxide (CO2) concentration can dictate plant growth and development and shape plant evolution. For paired populations of 31 Arabidopsis accessions, respectively, grown under 100 or 380 ppm CO2, we compared phenotypic traits related to vegetative growth and flowering time. Four accessions showed the least variation in measured growth traits between 100 ppm CO2 and 380 ppm CO2 conditions, though all accessions exhibited a dwarf stature with reduced biomass under low CO2. Our comparison of accessions also incorporated the altitude (indicated in meters) above sea level at which they were originally collected. Notably, An-1 (50 m), Est (50 m), Ws-0 (150 m), and Ler-0 (600 m) showed the least differences (lower decrease or increase) between treatments in flowering time, rosette leaf number, specific leaf weight, stomatal density, and less negative δ13C values. When variations for all traits and seedset were considered together, Ws-0 exhibited the least change between treatments. Our results showed that physiological and phenotypic responses to low CO2 varied among these accessions and did not correlate linearly with altitude, thus suggesting that slower growth or smaller stature under ambient CO2 may potentially belie a fitness advantage for sustainable growth under low CO2 availability.

PMID:33817279 | PMC:PMC7874586 | DOI:10.1515/biol-2020-0095

PeerJ Comput Sci. 2021 Jan 28;7:e363. doi: 10.7717/peerj-cs.363. eCollection 2021.

ABSTRACT

High throughput multi-omics data generation coupled with heterogeneous genomic data fusion are defining new ways to build computational inference models. These models are scalable and can support very large genome sizes with the added advantage of exploiting additional biological knowledge from the integration framework. However, the limitation with such an arrangement is the huge computational cost involved when learning from very large datasets in a sequential execution environment. To overcome this issue, we present a multiple kernel learning (MKL) based gene regulatory network (GRN) inference approach wherein multiple heterogeneous datasets are fused using MKL paradigm. We formulate the GRN learning problem as a supervised classification problem, whereby genes regulated by a specific transcription factor are separated from other non-regulated genes. A parallel execution architecture is devised to learn a large scale GRN by decomposing the initial classification problem into a number of subproblems that run as multiple processes on a multi-processor machine. We evaluate the approach in terms of increased speedup and inference potential using genomic data from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens. The results thus obtained demonstrate that the proposed method exhibits better classification accuracy and enhanced speedup compared to other state-of-the-art methods while learning large scale GRNs from multiple and heterogeneous datasets.

PMID:33817013 | PMC:PMC7924726 | DOI:10.7717/peerj-cs.363

Med J Islam Repub Iran. 2020 Dec 30;34:178. doi: 10.47176/mjiri.34.178. eCollection 2020.

ABSTRACT

Background: The aim of this study was to investigate the effectiveness of bone marrow-derived cells (BMC) technology in patients with heart failure and compare it with alternative therapies, including drug therapy, cardiac resynchronization therapy pacemaker (CRT-P), cardiac resynchronization therapy defibrillator (CRT-D). Methods: A systematic review study was conducted to identify all clinical studies published by 2017. Using keywords such as "Heart Failure, BMC, Drug Therapy, CRT-D, CRT-P" and combinations of the mentioned words, we searched electronic databases, including Scopus, Cochrane Library, and PubMed. The quality of the selected studies was assessed using the Cochrane Collaboration's tool and the Newcastle-Ottawa. The primary and secondary end-points were left ventricular ejection fraction (LVEF) (%), failure cases (Number), left ventricular end-systolic volume (LVES) (ml), and left ventricular end-diastolic volume (LVED) (ml). Random-effects network meta-analyses were used to conduct a systematic comparison. Statistical analysis was done using STATA. Results: This network meta-analysis covered a total of 57 final studies and 6694 patients. The Comparative effectiveness of BMC versus CRT-D, Drug, and CRT-P methods indicated the statistically significant superiority of BMC over CRT-P (6.607, 95% CI: 2.92, 10.29) in LVEF index and overall CRT-P (-13.946, 95% CI: -18.59, -9.29) and drug therapy (-4.176, 95% CI: -8.02, -.33) in LVES index. In addition, in terms of LVED index, the BMC had statistically significant differences with CRT-P (-10.187, 95% CI: -18.85, -1.52). BMC was also dominant to all methods in failure cases as a final outcome and the difference was statistically significant i.e. BMC vs CRT-D: 0.529 (0.45, 0.62) and BMC vs Drug: 0.516 (0.44, 0.60). In none of the outcomes, the other methods were statistically more efficacious than BMC. The BMC method was superior or similar to the other methods in all outcomes. Conclusion: The results of this study showed that the BMC method, in general, and especially in terms of failure cases index, had a higher level of clinical effectiveness. However, due to the lack of data asymmetry, insufficient data and head-to-head studies, BMC in this meta-analysis might be considered as an alternative to existing treatments for heart failure.

PMID:33816377 | PMC:PMC8004572 | DOI:10.47176/mjiri.34.178

Front Cell Infect Microbiol. 2021 Mar 17;11:641920. doi: 10.3389/fcimb.2021.641920. eCollection 2021.

ABSTRACT

Pseudomonas aeruginosa is a biofilm-forming opportunistic pathogen which causes chronic infections in immunocompromised patients and leads to high mortality rate. It is identified as a common coinfecting pathogen in COVID-19 patients causing exacerbation of illness. In our hospital, P. aeruginosa is one of the top coinfecting bacteria identified among COVID-19 patients. We collected a strong biofilm-forming P. aeruginosa strain displaying small colony variant morphology from a severe COVID-19 patient. Genomic and transcriptomic sequencing analyses were performed with phenotypic validation to investigate its adaptation in SARS-CoV-2 infected environment. Genomic characterization predicted specific genomic islands highly associated with virulence, transcriptional regulation, and DNA restriction-modification systems. Epigenetic analysis revealed a specific N6-methyl adenine (m6A) methylating pattern including methylation of alginate, flagellar and quorum sensing associated genes. Differential gene expression analysis indicated that this isolate formed excessive biofilm by reducing flagellar formation (7.4 to 1,624.1 folds) and overproducing extracellular matrix components including CdrA (4.4 folds), alginate (5.2 to 29.1 folds) and Pel (4.8-5.5 folds). In summary, we demonstrated that P. aeuginosa clinical isolates with novel epigenetic markers could form excessive biofilm, which might enhance its antibiotic resistance and in vivo colonization in COVID-19 patients.

PMID:33816347 | PMC:PMC8010185 | DOI:10.3389/fcimb.2021.641920

Front Oncol. 2021 Mar 17;11:617621. doi: 10.3389/fonc.2021.617621. eCollection 2021.

ABSTRACT

The metastasis of nasopharyngeal carcinoma (NPC) is a complex process associated with oncogenic dysfunction, the deciphering of which remains a challenge and requires more in-depth studies. Y-box protein 3 (YBX3) is a DNA/RNA binding protein associated with gene transcription, DNA repair, and the progression of various diseases. However, whether and how YBX3 affects the metastasis of NPC remains unknown. Thus, in this study, we aimed to investigate the role of YBX3 in the metastasis of NPC and determine its underlying mechanism. Interestingly, it was found that the expression of YBX3, which was associated with NPC metastasis, was upregulated in the clinical NPC tissues and cell lines. Moreover, we found that knockdown of YBX3 expression by lentivirus shRNA significantly suppressed NPC cells migration in vitro and metastasis in vivo. Mechanistically, RNA sequencing results suggested that the genes regulated by YBX3 were significantly enriched in cell adhesion molecules, cAMP signaling pathway, calcium signaling pathway, focal adhesion, PI3K/AKT signaling pathway, Ras signaling pathway, Rap1 signaling pathway, NF-κB signaling pathway, and Chemokine signaling pathway. Of these, PI3K/AKT signaling pathway contained the most genes. Accordingly, YBX3 knockdown decreased the activation of PI3K/AKT signaling pathway, thereby inhibit epithelial-to-mesenchymal transition (EMT) and MMP1. These results have demonstrated that YBX3 are involved in the metastasis of NPC through regulating PI3K/AKT signaling pathway, and serve as a potential therapeutic target for patients with NPC.

PMID:33816248 | PMC:PMC8010247 | DOI:10.3389/fonc.2021.617621

Comput Struct Biotechnol J. 2021;19:1672-1683. doi: 10.1016/j.csbj.2021.03.028. Epub 2021 Mar 26.

ABSTRACT

SARS-CoV-2 and Influenza co-infection turned out to be a huge threat in recent times. The clinical presentation and disease severity is common in both the infection condition. The present paper deals with studying co-infection model system through systems biology approaches. Understanding signaling regulation in COVID-19 and co-infection model systems aid in the development of network-based models thereby suggesting intervention points for therapeutics. This paper highlights the aim of revealing such perturbations to decipher opportune mediating cross talks characterizing the deadly viral disease. The comparative analysis of both the models reveals major signaling protein NFκB and STAT1 playing a crucial role in establishing co-infection. By targeting these proteins at cellular level, it might help modulating the release of potent pro-inflammatory cytokines thereby taming the severity of the disease symptoms. Mathematical models developed here are precisely tailored and serves as a first step towards co-infection model offering flexibility and pitching towards therapeutic investigation.

PMID:33815692 | PMC:PMC7997053 | DOI:10.1016/j.csbj.2021.03.028