METHODS: In this study, the metabolic responses of C. glabrata under acetate growth condition was explored using high-throughput transcriptomic and proteomic approaches.
RESULTS: Collectively, a total of 1482 transcripts (26.96%) and 242 proteins (24.69%) were significantly up- or down-regulated. Both transcriptome and proteome data revealed that the regulation of alternative carbon metabolism in C. glabrata resembled other fungal pathogens such as Candida albicans and Cryptococcus neoformans, with up-regulation of many proteins and transcripts from the glyoxylate cycle and gluconeogenesis, namely isocitrate lyase (ICL1), malate synthase (MLS1), phosphoenolpyruvate carboxykinase (PCK1) and fructose 1,6-biphosphatase (FBP1). In the absence of glucose, C. glabrata shifted its metabolism from glucose catabolism to anabolism of glucose intermediates from the available carbon source. This observation essentially suggests that the glyoxylate cycle and gluconeogenesis are potentially critical for the survival of phagocytosed C. glabrata within the glucose-deficient macrophages.
CONCLUSION: Here, we presented the first global metabolic responses of C. glabrata to alternative carbon source using transcriptomic and proteomic approaches. These findings implicated that reprogramming of the alternative carbon metabolism during glucose deprivation could enhance the survival and persistence of C. glabrata within the host.
Methods: In this present study, two protein extractions methods were performed to analyze female Ae. aegyti proteome, via TCA acetone precipitation extraction method and a commercial protein extraction reagent CytoBusterTM. Then, protein identification was performed by LC-ESI-MS/MS and followed by functional protein annotation analysis.
Results: The CytoBusterTM reagent gave the highest protein yield with a mean of 475.90 µg compared to TCA acetone precipitation extraction showed 283.15 µg mean of protein. LC-ESI-MS/MS identified 1,290 and 890 proteins from the CytoBusterTM reagent and TCA acetone precipitation, respectively. When comparing the protein class categories in both methods, there were three additional categories for proteins identified using CytoBusterTM reagent. The proteins were related to scaffold/adaptor protein (PC00226), protein binding activity modulator (PC00095) and intercellular signal molecule (PC00207). In conclusion, the CytoBusterTM protein extraction reagent showed a better performance for the extraction of proteins in term of the protein yield, proteome coverage and extraction speed.
METHODS: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF.
RESULTS: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-β binding protein-4, and follistatin-related protein-3, as well.
CONCLUSIONS: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.
MATERIALS AND METHODS: Total RNA was extracted from three formalin-fixed paraffin-embedded (FFPE) samples each of normal cervix, HPV-infected low-grade squamous intraepithelial lesion (LSIL), high-grade SIL (HSIL) and squamous cell carcinoma (SCC). Transcriptomic profiling by microarrays was conducted followed by downstream Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.
RESULTS: We examined the difference in GOs enriched for each transition stage from normal cervix to LSIL, HSIL, and SCC, and found 307 genes to be differentially expressed. In the transition from normal cervix to LSIL, the extracellular matrix (ECM) genes were significantly downregulated. The MHC class II genes were significantly upregulated in the LSIL to HSIL transition. In the final transition from HSIL to SCC, the immunoglobulin heavy locus genes were significantly upregulated and the ECM pathway was implicated.
CONCLUSION: Deregulation of the immune-related genes including MHC II and immunoglobulin heavy chain genes were involved in the transitions from LSIL to HSIL and SCC, suggesting immune escape from host anti-tumour response. The extracellular matrix plays an important role during the early and late stages of cervical carcinogenesis.
RESULTS: Firstly, from the expression profiles of Na+/K+/2Cl- cotransporter, chloride channel protein 2, and ABC transporter, it turned out that the 24 h might be the most influenced duration in the short-term stress. We collected megalopa under different salinity for 24 h and then submitted to mRNA profiling. Totally, 57.87 Gb Clean Data were obtained. The comparative genomic analysis detected 342 differentially expressed genes (DEGs). The most significantly DEGs include gamma-butyrobetaine dioxygenase-like, facilitated trehalose transporter Tret1, sodium/potassium-transporting ATPase subunit alpha, rhodanese 1-like protein, etc. And the significantly enriched pathways were lysine degradation, choline metabolism in cancer, phospholipase D signaling pathway, Fc gamma R-mediated phagocytosis, and sphingolipid signaling pathway. The results indicate that in the short-term salinity stress, the megalopa might regulate some mechanism such as metabolism, immunity responses, osmoregulation to adapt to the alteration of the environment.
CONCLUSIONS: This study represents the first genome-wide transcriptome analysis of S. paramamosain megalopa for studying its stress adaption mechanisms under different salinity. The results reveal numbers of genes modified by salinity stress and some important pathways, which will provide valuable resources for discovering the molecular basis of salinity stress adaptation of S. paramamosain larvae and further boost the understanding of the potential molecular mechanisms of salinity stress adaptation for crustacean species.