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PubMed2006

MIPS: analysis and annotation of proteins from whole genomes in 2005.

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

Animals↗

PubMed2026

Identification of a necroptosis-related lncRNA prognostic signature and the hub RBP HNRNPK in esophageal squamous cell carcinoma.

ObjectiveEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with poor prognosis. Necroptosis is important for tumor immunity, but its role in ESCC remains unclear. This retrospective bioinformatics study aimed to investigate the prognostic value of necroptosis-related long non-coding RNAs (lncRNAs) and to identify key lncRNA-binding proteins (RBPs) in ESCC patients.MethodsRNA transcriptome and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Necroptosis-related lncRNAs were identified through correlation analysis with necroptosis-related genes, subjected to consensus cluster analysis, and used to construct a prognostic risk model via least absolute shrinkage and selection operator (LASSO) regression. The hub RBP was experimentally validated by quantitative polymerase chain reaction (qPCR) using 30 pairs of ESCC and adjacent normal tissues from patients who underwent surgical resection.ResultsA total of 30 necroptosis-related lncRNAs were significantly correlated with overall survival (OS). The upregulated lncRNAs in the risk model were associated with high immune scores, innate immune cell infiltration, cluster 2 classification, and advanced T-stage disease (p < 0.05). Three hub RBPs (HNRNPA1, HNRNPC, and HNRNPK) were identified through protein-protein interaction network analysis. qPCR confirmed that HNRNPK was significantly overexpressed in ESCC tissues compared to adjacent normal tissues (p < 0.05).ConclusionsThe necroptosis-related lncRNA risk model is an independent prognostic factor for ESCC patients. HNRNPK was identified as a hub RBP significantly overexpressed in ESCC tissues. We hypothesize that HNRNPK may promote tumor progression through regulating proto-oncogene expression or modulating the immune microenvironment, though this requires further mechanistic validation.

Humans↗

PubMed2005

[Origin and genetic diversity of Mongolian and Chinese sheep using mitochondrial DNA D-loop sequences].

To determine the origin and gene diversity of the Chinese and Mongolian domestic sheep, a partial fragment of mitochondrial DNA D-loop was sequenced for total number of 314 individuals from nine Chinese sheep populations and 11 Mongolian sheep populations. The results show no difference in nucleotide composition between Chinese and Mongolian sheep mtDNA D-loop sequences. However, more variables were identified in Mongolian sheep (26.85% of the sites) than that in Chinese sheep (24.22%). In China, mtDNA haplotype diversity was the highest in Qinghai Tibetan sheep, followed then by Gansu Tibetan sheep, Gansu Alpine Merino, Qinghai Merino, Gannan Tibetan sheep, Small-tailed Han sheep, Tan sheep, Hu sheep and Minxian Black Fur sheep. In Mongolian sheep, mtDNA haplotype diversity was the highest in Bayad and Baidrag populations and the lowest in the Gobi-Altai population. In general, Mongolian sheep have a richer genetic diversity than the Chinese ones with larger number of haplotypes (86.06% (142/165) versus 78.83% (108/137)), higher haplotype diversity (Hd; 0.976 versus 0.936), higher nucleotide diversity (Pi (pi); 0. 036 versus 0.034) and higher average number of nucleotide differences (k; 23.50 versus 22.48). Phylogenetic analysis of the 217 haplotypes identified in both Mongolian and Chinese sheep supported the same origin of their domestication with three distinct maternal lineages defined as major haplotypes A, B and C, of which haplotype A are the commonest in all Chinese sheep populations and in the majority of Mongolian sheep populations (9/11) with an average frequency of 58.73%, followed by haplotype B present in eight of Chinese population and in all Mongolian sheep populations with an average frequency of 24.68%, and haplotype C present in eight Chinese and in 10 Mongolian sheep populations with an average frequency of 16.59%. Further network analysis of the phylogenetic relationship of the 87 haplotypes identified from 91 sequences retrieved from GenBank together with the 217 haplotypes detected in this study reveals clearly four distinct lineages with the European mouflon (O. musimon) mixed into one of the lineages (haplotype B). There is no evidence of contribution of Argali sheep (O. ammon), O. vignei bochariensis and/or O. ammon nigrimontana to the maternal origin of both Mongolian and Chinese domestic sheep.

Animals↗

PubMed2003

Systematic quantification of complex metabolic flux networks using stable isotopes and mass spectrometry.

Metabolic fluxes provide a detailed metric of the cellular metabolic phenotype. Fluxes are estimated indirectly from available measurements and various methods have been developed for this purpose. Of particular interest are methods making use of stable isotopic tracers as they enable the estimation of fluxes at a high resolution. In this paper, we present data validating the use of mass spectrometry (MS) for the quantification of complex metabolic flux networks. In the context of the lysine biosynthesis flux network of Corynebacterium glutamicum (ATCC 21799) under glucose limitation in continuous culture, operating at 0.1 x h(-1) after the introduction of 50% [1-13C]glucose, we deploy a bioreaction network analysis methodology for flux determination from mass isotopomer measurements of biomass hydrolysates, while thoroughly addressing the issues of measurement accuracy, flux observability and data reconciliation. The analysis enabled the resolution of the involved anaplerotic activity of the microorganism using only one labeled substrate, the determination of the range of most of the exchange fluxes and the validation of the flux estimates through satisfaction of redundancies. Specifically, we determined that phosphoenolpyruvate carboxykinase and synthase do not carry flux at these experimental conditions and identified a high futile cycle between oxaloacetate and pyruvate, indicating a highly active in vivo oxaloacetate decarboxylase. Both results validated previous in vitro activity measurements. The flux estimates obtained passed the chi2 statistical test. This is a very important result considering that prior flux analyses of extensive metabolic networks from isotopic measurements have failed criteria of statistical consistency.

Amino Acids↗

PubMed2025

How Does Tendon Region, Donor, and the Presence of Disease Affect Protein Composition of the Achilles Tendon?

BACKGROUND: Response to treatment for tendinopathy is variable, which may reflect variability in underlying etiology and capacity for the tendon to respond to treatment. Understanding variability in tendon protein composition may help improve our understanding of the mechanistic underpinnings of painful tendon degeneration and inform treatment targets. QUESTIONS/PURPOSES: (1) What factors (tendon region, individual characteristics, presence of disease) contribute to protein compositional (proteomic) and structural variation in human Achilles tendons? (2) What compositional changes characterize tendinopathy, and what protein interactions might contribute to tendon degeneration? (3) How does diabetes influence tendon composition, and what mechanisms might underlie tendon dysfunction in individuals with diabetes? METHODS: In this exploratory, cross-sectional study, human Achilles tendon specimens were obtained from individuals with (diabetes group, n = 5) or without diabetes (control group, n = 5) undergoing lower extremity amputation and from individuals undergoing tendon debridement surgeries for tendinopathy (tendinopathy group, n = 8). Specimens were collected between 2019 and 2023. Protein abundances were quantified and analyzed using mass spectrometry, hierarchical clustering, and principal component analysis. To evaluate the role of tendon region and donor on tendon protein compositional variability, we assessed proteomic differences between three regions in nontendinopathic tendons from three individuals. To identify the contribution of disease (that is, presence of tendinopathy or diabetes) on protein composition, we compared tendons from the tendinopathy (n = 8 [2 males, 6 females], mean ± SD age 48 ± 11 years), diabetes (n = 5 [3 males, 2 females], age 54 ± 9 years), and control (n = 5 [3 males, 2 females], age 42 ± 12 years) groups. Proteomic differences associated with tendinopathy and diabetes were further examined using functional enrichment and protein-protein interaction network analysis. RESULTS: Variability in tendon protein composition was primarily from presence of disease, followed by donor and then tendon region. Protein composition distinguished tendons with tendinopathy from controls, with 311 proteins differentially expressed (152 overexpressed and 159 underexpressed; fold change ≥ 1.5, p < 0.05) and higher Bonar scores indicating greater degeneration (mean ± SD Bonar score tendinopathy group 8.6 ± 1.2 versus control group 2.1 ± 0.7; p = 0.01). Pathway analysis identified dysregulation in extracellular matrix remodeling (TIMP1, MMP3, MMP10), inflammatory response (TNF-α, EGFR1), and metabolic reprogramming. Tendons from individuals with diabetes exhibited minimal proteomic changes compared with the control group, with 66 differentially expressed proteins (31 overexpressed and 35 underexpressed; fold change ≥ 1.5, p < 0.05) with no histopathologic differences between diabetes and control group tendons (mean ± SD Bonar score diabetes group 3.4 ± 1.0 versus control group 2.1 ± 0.7; p = 0.19). Tendons in the diabetes group showed reductions in Type I collagen, enrichment of pathways associated with fibrosis and metabolic dysfunction, and inflammatory pathways associated with α 6 β 4 integrin. CONCLUSION: Our findings indicate that Achilles tendon composition primarily differs based on disease etiology, with tendinopathy showing extensive extracellular matrix disruption and inflammatory activity, whereas tendons from individuals with diabetes exhibit more subtle compositional changes. This distinction suggests that tendinopathy may require targeted interventions addressing tissue remodeling and inflammation, whereas diabetes may predispose tendons to injury but not directly result in degeneration. Understanding these protein compositional variations can help refine hypotheses about disease progression, treatment response, and potential therapeutic targets. CLINICAL RELEVANCE: While proteomic analysis is not currently a part of routine clinical assessment, these findings provide a framework for identifying protein markers that may aid in early diagnosis or patient stratification to improve treatment alignment. Future studies could determine whether these proteomic changes correlate with treatment response and further inform our understanding of early-stage degeneration from chronic disease. By bridging molecular findings with clinical presentation, this study lays the groundwork for future research on precision medicine approaches for tendon disorders, with the long-term goal of tailoring treatment based on both biological and symptomatic characteristics.

Humans↗

PubMed2026

Evidence for dual pathways of Tc1/mariner domestication in Drosophila.

BACKGROUND: The domestication of transposable elements is a key source of evolutionary innovation, yet the pathways by which their functional modules are repurposed by the host remain poorly understood. The Tc1/mariner superfamily is a widespread group of DNA transposons, but the prevalence and patterns of their domestication are underexplored. RESULTS: We performed a systematic genomic screen across 43 drosophilid species using stringent criteria for molecular domestication. This analysis identified five high-confidence, evolutionarily conserved genes derived from Tc1/mariner transposases. Phylogenetic and structural analyses suggest domestication via two distinct molecular pathways: co-option of the DNA-binding module and co-option of the catalytic domain. The DNA-binding module pathway includes CG4570, the previously known genes cag and toy (the latter fused with a homeodomain), and a lineage-restricted gene in the Drosophila obscura group that exhibits signatures of recent domestication. In contrast, the catalytic domain pathway is represented solely by CG14478. Structural modeling reveals that CG14478 protein preserves a canonical DDE endonuclease fold. Co-expression network analysis suggests potential cellular roles of these genes: CG14478 is linked to RNA/chromatin-related processes, CG4570 to cell cycle/chromosome functions, cag to ciliary and nuclear functions, and toy to neuronal development. CONCLUSIONS: This study establishes a stringent framework for identifying domesticated TEs, demonstrating that Tc1/mariner elements are co-opted via two distinct pathways: retention of either catalytic or DNA-binding modules. Our findings suggest that domestication is a dynamic continuum, ranging from recent, lineage-specific events to ancient, conserved genes, and underscore how genomic conflict with TEs can drive eukaryotic evolution and regulatory complexity.

Animals↗

PubMed1981

The effects of refeeding after varying periods of neonatal undernutrition on the morphology of Purkinje cells in the cerebellum of the rat.

Undernutrition of the rat for the first 30 days of postnatal life is known to permanently alter Purkinje cell (PC) dendritic morphology. The effects of earlier nutritional rehabilitation have not previously been determined. Neonatal rat pups were undernourished by limiting their access to the lactating dam. After 10, 15, or 20 days of food restriction, animals were either killed for histological comparison with normally fed controls, or provided with ad libitum food until 80 dpp, and then killed. Network analysis of Golgi Cox impregnated PCs from the undernourished animals revealed alterations in dendritic length, segment frequency, and branching pattern, which first became apparent at 15 dpp, accompanied by a reduction in the number of granule cells (GCs) per PC. If undernourished animals were refed from 10 or 15 days, however, the total lengths and segment frequencies of their PC trees were indistinguishable from those of controls at 80 dpp, although the 15-day group showed persistent topological alterations. The GC:PC ratios of these refed groups were also found to be similar to those of the controls. In animals refed after 20 days of undernutrition, network size remained reduced, as did the GC:PC ratio. The different degrees of recovery of PC dendritic field parameters recorded in the refed animals could be related either to enhanced GC replication afforded by refeeding, or to the existence of intrinsic mechanisms which limit the growth capacity of the PC dendrites.

Animals↗

PubMed2004

Towards developing a protein infrared spectra databank (PISD) for proteomics research.

Fourier transform infrared (FTIR) spectroscopy is an attractive tool for proteomics research as it can be used to rapidly characterize protein secondary structure in aqueous solution. Recently, a number of secondary structure prediction methods based on reference sets of FTIR spectra from proteins with known structure from X-ray crystallography have been suggested. These prediction methods, often referred to as pattern recognition based approaches, demonstrated good prediction accuracy using some error measure, e.g., the standard error of prediction (SEP). However, to avoid possible adverse effects from differences in recording, the analysis has been mostly based on reference sets of FTIR spectra from proteins recorded in one laboratory only. As a result, these studies were based on reference sets of FTIR spectra from a limited number of proteins. Pattern recognition based approaches, however, rely on reference sets of FTIR spectra from as many proteins as possible representing all possible band shape variation to be related to the diversity of protein structural classes. Hence, if we want to build reliable pattern recognition based systems to support proteomics research, which are capable of making good predictions from spectral data of any unknown protein, one common goal should be to build a comprehensive protein infrared spectra databank (PISD) containing FTIR spectra of proteins of known structure. We have started the process of developing a comprehensive PISD composed of spectra recorded in different laboratories. As part of this work, here we investigate possible effects on prediction accuracy achieved by a neural network analysis when using reference sets composed of FTIR spectra from different laboratories. Surprisingly low magnitude of difference in SEPs throughout all our experiments suggests that FTIR spectra recorded in different laboratories may be safely combined into one reference set with only minor deterioration of prediction accuracy in the worst case.

Algorithms↗

PubMedDate not supplied

On-line metabolic pathway analysis based on metabolic signal flow diagram.

In this work, an integrated modeling approach based on a metabolic signal flow diagram and cellular energetics was used to model the metabolic pathway analysis for the cultivation of yeast on glucose. This approach enables us to make a clear analysis of the flow direction of the carbon fluxes in the metabolic pathways as well as of the degree of activation of a particular pathway for the synthesis of biomaterials for cell growth. The analyses demonstrate that the main metabolic pathways of Saccharomyces cerevisiae change significantly during batch culture. Carbon flow direction is toward glycolysis to satisfy the increase of requirement for precursors and energy. The enzymatic activation of TCA cycle seems to always be at normal level, which may result in the overflow of ethanol due to its limited capacity. The advantage of this approach is that it adopts both virtues of the metabolic signal flow diagram and the simple network analysis method, focusing on the investigation of the flow directions of carbon fluxes and the degree of activation of a particular pathway or reaction loop. All of the variables used in the model equations were determined on-line; the information obtained from the calculated metabolic coefficients may result in a better understanding of cell physiology and help to evaluate the state of the cell culture process.

Models, Biological↗

PubMed2026

Domesticated Argania spinosa in Eastern Morocco: HPLC-DAD/GC-MS Chemical Profiling, Antioxidant and Antidiabetic Activities, and Network Pharmacology-Guided Molecular Docking.

The argan tree (Argania spinosa) is an endemic Moroccan species known for its primary product, argan oil, which possesses exceptional nutritional and medicinal properties. The current study aimed to evaluate and compare the antidiabetic and antioxidant activities of argan oil obtained from the introduced and native argan tree in eastern Morocco, to analyze its chemical composition using HPLC-DAD and GC-MS, and to investigate the molecular mechanisms behind the obtained pharmacological activities through an in silico pharmacological networking and molecular docking study. The results revealed that argan oil from all three regions of Morocco (Oujda, Agadir, and Chouihya) is rich in oleic and linoleic acids as major constituents, along with the presence of significant tocopherols. Regarding the antioxidant assays, including DPPH radical scavenging and iron-reducing power tests, argan oil from Oujda exhibited the highest activity, with the lowest IC50 values of 15.25 ± 0.022 mg/mL and 28.5 ± 1.7 mg/mL, respectively. Concerning the antidiabetic activity, we found that oil from Chaouihya showed the strongest α-amylase inhibition, while Oujda oil had the highest antiglycation activity, indicating that even introduced argan trees retain potent bioactivity. The results of the in silico investigation suggested that tocopherols may contribute to the antioxidant and antidiabetic potential of argan oil, showing predicted antioxidant activity (Pa = 0.843-0.967) and favorable binding affinities toward iNOS (ΔG = -9.3 kcal mol-1) and α-glucosidase (ΔG = -8.2 kcal mol-1). The identified fatty acids also showed predicted insulin-promoting activity (Pa = 0.59-0.75) and moderate enzyme-binding potential. Pharmacological network analysis identified 51 shared genes associated with antioxidant, antidiabetic, and argan-related targets, with enrichment of the AGE-RAGE signaling pathway. These computational findings provide possible molecular associations that may help explain the observed biological activities, although they remain predictive and require experimental validation. Overall, the in silico analysis suggests that tocopherols could be among the contributors to the multi-target profile of Argania spinosa oil, while fatty acids may provide complementary effects related to glycemic regulation.

Sapotaceae↗

PubMed1999

Analysis and assessment of ab initio three-dimensional prediction, secondary structure, and contacts prediction.

CASP3 saw a substantial increase in the volume of ab initio 3D prediction data, with 507 datasets for fifteen selected targets and sixty-one groups participating. As with CASP2, methods ranged from computationally intensive strategies that attempt to recreate the physical and chemical forces involved in protein folding to the more recent knowledge-based approaches. These exploit information from the structure databases, extracting potentially similar fragments and/or distance constraints derived from multiple sequence alignments. The knowledge-based approaches generally gave more consistently successful predictions across the range of targets, particularly that of the Baker group (Bystroff and Baker, J Mol Biol 1998;281:565-577; Simons et al. Proteins Suppl 1999;3:171-176), which used a fragment library. In the secondary structure prediction category, the most successful approaches built on the concepts used in PHD (Rost et al. Comput Appl Biosci 1994;10:53-60), an accepted standard in this field. Like PHD, they exploit neural networks but have different strategies for incorporating multiple sequence data or position-dependent weight matrices for training the networks. Analysis of the contact data, for which only six groups participated, suggested that as yet this data provides a rather weak signal. However, in combination with other types of prediction data it can sometimes be a useful constraint for identifying the correct structure.

Animals↗

PubMed2026

NR3C1 Modulates Wnt Signalling to Influence the Invasiveness and Immune Features of Nonfunctioning Invasive Pituitary Adenomas.

Pituitary adenomas (PAs) are common intracranial tumours, and invasiveness in nonfunctioning invasive pituitary adenomas (NIPAs) predicts poor prognosis. The molecular mechanisms driving this phenotype remain unclear. This study explored the role of nuclear receptor subfamily 3 group C member 1 (NR3C1) in NIPA invasiveness and its regulation of Wnt signalling. mRNA expression profiles of 32 PA samples were generated by RNA-seq, and proteomic data from 19 samples were obtained by mass spectrometry. Immune-related differentially expressed genes (DEGs) were retrieved from GeneCards. Weighted gene coexpression network analysis identified modules and hub genes linked to invasiveness, while machine learning methods (support vector machine, LASSO, random forest) prioritised key genes. Gene set enrichment analysis (GSEA) assessed pathways associated with candidate gene expression. NR3C1 expression and function were validated by immunohistochemistry, Western blotting and invasion assays. Integration of transcriptomic, proteomic and immune-related datasets yielded 11 overlapping genes, with NR3C1 emerging as the top candidate. NR3C1 was significantly upregulated in NIPAs and demonstrated good discriminatory power by ROC analysis. GSEA associated high NR3C1 expression with Wnt pathway activation. Functional experiments confirmed that NR3C1 overexpression enhances the invasive capacity of PA cells. NR3C1 promotes the invasive phenotype of NIPAs by activating Wnt signalling. These findings suggest NR3C1 as a potential biomarker and therapeutic target for invasive pituitary adenomas.

Humans↗

PubMed2026

Comparative transcriptomic analysis of the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress.

To investigate the differences in molecular responses between the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress, a 30-day chronic stress experiment was conducted with a control group and a stress group. Transcriptomic analysis of the gills and hepatopancreas was performed using Illumina sequencing; differentially expressed genes (DEGs) were identified, and GO, KEGG, GSEA, PPI, and RT-qPCR validation were carried out. The results showed that 196 DEGs (161 up-regulated and 35 down-regulated) were identified in the gills, and 287 DEGs (199 up-regulated and 88 down-regulated) in the hepatopancreas, with only 18 DEGs shared between the two tissues. DEGs in the gills were enriched in oxidoreductase activity, glycerophospholipid metabolism, and tyrosine metabolism; DEGs in the hepatopancreas were enriched in lipid transporter activity, phagosome, ECM-receptor interaction, and riboflavin metabolism. GSEA revealed significant suppression of the mTOR pathway in the gills and the Polycomb complex pathway in the hepatopancreas. PPI network analysis identified hub genes P5CS and eEF2 in the gills, and PER, TUBB1, SHMT, and TUBB4B in the hepatopancreas. RT-qPCR validation was consistent with the RNA-seq results (R2 = 0.764). This study indicates that, under chronic nitrite stress, the gill response is centered on redox regulation and inhibition of growth metabolism, whereas the hepatopancreas response primarily involves lipid transport, cytoskeletal remodeling, and phagosome activation. The two tissues synergistically adapt through fundamental biosynthetic and motor protein pathways. This research provides molecular evidence for deciphering the nitrite tolerance mechanisms in freshwater-cultured shrimp.

Animals↗

PubMed2025

Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes.

We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72, 38 GRN, and 25 MAPT) and 55 symptomatic (27 C9orf72, 17 GRN, and 11 MAPT) mutation carriers as well as 76 mutation-negative controls ("noncarriers"). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer's disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.

Humans↗

PubMed2006

High-throughput identification of IMCD proteins using LC-MS/MS.

The inner medullary collecting duct (IMCD) is an important site of vasopressin-regulated water and urea transport. Here we have used protein mass spectrometry to investigate the proteome of the IMCD cell and how it is altered in response to long-term vasopressin administration in rats. IMCDs were isolated from inner medullas of rats, and IMCD proteins were identified by liquid chromatography/tandem mass spectrometry (LC-MS/MS). We present a WWW-based "IMCD Proteome Database" containing all IMCD proteins identified in this study (n = 704) and prior MS-based identification studies (n = 301). We used the isotope-coded affinity tag (ICAT) technique to identify IMCD proteins that change in abundance in response to vasopressin. Vasopressin analog (dDAVP) or vehicle was infused subcutaneously in Brattleboro rats for 3 days, and IMCDs were isolated for proteomic analysis. dDAVP and control samples were labeled with different cleavable ICAT reagents (mass difference 9 amu) and mixed. This was followed by one-dimensional SDS-PAGE separation, in-gel trypsin digestion, biotin-avidin affinity purification, and LC-MS/MS identification and quantification. Responses to vasopressin for a total of 165 proteins were quantified. Quantification, based on semiquantitative immunoblotting of 16 proteins for which antibodies were available, showed a high degree of correlation with ICAT results. In addition to aquaporin-2 and gamma-epithelial Na channel (gamma-ENaC), five of the immunoblotted proteins were substantially altered in abundance in response to dDAVP, viz., syntaxin-7, Rap1, GAPDH, heat shock protein (HSP)70, and cathepsin D. A 28-protein vasopressin signaling network was constructed using literature-based network analysis software focusing on the newly identified proteins, providing several new hypotheses for future studies.

Animals↗

PubMed2026

Deciphering differential mRNA and lncRNA expression profiles in response to PEG simulated drought stress in cucumber (Cucumis sativus L.).

Cucumber (Cucumis sativus L.), a vital fruit vegetable of the Cucurbitaceae family, originated in India ∼ 3000 years ago. It is widely used in the culinary, therapeutic, and cosmetic sectors. Cucumber cultivation is significantly impacted by drought stress, especially in arid and semi-arid regions. This study investigates the molecular response to drought using two contrasting cucumber lines: WBC-23-2 (drought-tolerant) and DGPC-59 (drought-sensitive). Drought was simulated using polyethylene glycol (PEG), and effects on physiological and biochemical traits were evaluated. The tolerant line exhibited reduced leaf wilting and higher relative water content (RWC). Based on these physiological markers, transcriptomic profiling was employed to identify the underlying regulatory networks. Analysis identified 4,736 DEGs, suggesting that the tolerant line's superior resilience is driven by preferential activation of genes involved in photosynthesis and glutathione metabolism. Conversely, the sensitive genotype showed enrichment in organonitrogen compound catabolism and water deprivation response. This divergence is further reflected in the regulation of 155 transcription factors (TFs) across various families, indicating distinct regulatory architectures between the two lines. Additionally, 774 drought-responsive long non-coding RNAs (lncRNAs) were identified, acting via cis, trans, and competing endogenous RNA (ceRNA) mechanisms to modulate gene expression. Key candidate genes associated with drought tolerance included WAT1-related protein At5g64700, thaumatin-like protein, berberine bridge enzyme-like 18, probable WRKY transcription factor, and pathogenesis-related protein 1. This study reveals a complex regulatory network of mRNAs, lncRNAs, and TFs underlying drought response and provides a valuable foundation for breeding drought-resilient cucumber cultivars. A web-based genomic resource, CsDTDb, has been developed and made publicly available to facilitate future functional genomics studies related to drought tolerance in cucumber.

DEGs↗

PubMed1998

Dynamic nonlinear vago-sympathetic interaction in regulating heart rate.

Although the characteristics of the static interactions between the sympathetic and parasympathetic nervous systems in regulating heart rate have been well established, how the dynamic interaction modulates the heart rate response remains unknown. Thus, we investigated the dynamic interaction by estimating the transfer function from nerve stimulation to heart rate, using band-limited Gaussian white noise, in anesthetized rabbits. Concomitant tonic vagal stimulation at 5 and 10 Hz increased the gain of the transfer function relating dynamic sympathetic stimulation to heart rate by 55.0%+/-40.1% and 80.7%+/-50.5%, respectively (P < 0.05). Concomitant tonic sympathetic stimulation at 5 and 10 Hz increased the gain of the transfer function relating dynamic vagal stimulation to heart rate by 18.2%+/-17.9% and 24.1%+/-18.0%, respectively (P < 0.05). Such bidirectional augmentation was also observed during simultaneous dynamic stimulation of the sympathetic and vagal nerves independent of their stimulation patterns. Because of these characteristics, changes in sympathetic or vagal tone alone can alter the dynamic heart rate response to stimulation of the other nerve. We explained this phenomenon by assuming a sigmoidal static relationship between autonomic nerve activity and heart rate. To confirm this assumption, we identified the static and dynamic characteristics of heart rate regulation by a neural network analysis, using large-amplitude Gaussian white noise input. To examine the mechanism involved in the bidirectional augmentation, we increased cytosolic adenosine 3',5'-cyclic monophosphate (cAMP) at the postjunctional effector site by applying pharmacological interventions. The cAMP accumulation increased the gain of the transfer function relating dynamic vagal stimulation to heart rate. Thus, accumulation of cAMP contributes, at least in part, to the sympathetic augmentation of the dynamic vagal control of heart rate.

Animals↗

PubMed2006

Integrated gene expression profiling and linkage analysis in the rat.

The combined application of genome-wide expression profiling from microarray experiments with genetic linkage analysis enables the mapping of expression quantitative trait loci (eQTLs) which are primary control points for gene expression across the genome. This approach allows for the dissection of primary and secondary genetic determinants of gene expression. The cis-acting eQTLs in practice are easier to investigate than the trans-regulated eQTLs because they are under simpler genetic control and are likely to be due to sequence variants within the gene itself or its neighboring regulatory elements. These genes are therefore candidates both for variation in gene expression and for contributions to whole-body phenotypes, particularly when these are located within known and relevant physiologic QTLs. Multiple trans-acting eQTLs tend to cluster to the same genetic location, implying shared regulatory control mechanisms that may be amenable to network analysis to identify gene clusters within the same metabolic pathway. Such clusters may ultimately underlie development of individual complex, whole-body phenotypes. The combined expression and linkage approach has been applied successfully in several mammalian species, including the rat which has specific features that demonstrate its value as a model for studying complex traits.

Animals↗