protein markers
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2022 ◽  
Vol 199 ◽  
pp. 243-251
Francisco S.B. Mota ◽  
Kyria S. Nascimento ◽  
Messias V. Oliveira ◽  
Vinicius J.S. Osterne ◽  
Joana C.M. Clemente ◽  

2022 ◽  
Vol 18 (1) ◽  
Jie Pei ◽  
Rende Song ◽  
Pengjia Bao ◽  
Mancai Yin ◽  
Jiye Li ◽  

Abstract Background Ovarian follicle fluid (FF) as a microenvironment surrounding oocyte plays critical roles in physio-biochemical processes of follicle development and oocyte maturation. It is hypothesized that proteins in yak FF participate in the physio-biochemical pathways. The primary aims of this study were to find differentially expressed proteins (DEPs) between mature and immature FF, and to elucidating functions of the mature and immature FF in yak. Results The mature and immature FF samples were obtained from three healthy yaks that were nonpregnant, aged from four to five years, and free from any anatomical reproductive disorders. The FF samples were subjected to mass spectrometry with the isobaric tags for relative and absolute quantification (iTRAQ). The FF samples went through correlation analysis, principle component analysis, and expression pattern analysis based on quantification of the identified proteins. Four hundred sixty-three DEPs between mature and immature FF were identified. The DEPs between the mature and immature FF samples underwent gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and protein-protein interaction (PPI) analysis. The DEPs highly expressed in the mature FF mainly took parts in the complement and coagulation cascades, defense response, acute-phase response, response to other organism pathways to avoid invasion of exogenous microorganisms. The complement activation pathway contains eight DEPs, namely C2, C5, C6, C7, C9, C4BPA, CFH, and MBL2. The three DEPs, CATHL4, CHGA, and PGLYRP1, take parts in defense response pathway to prevent invasion of exogenetic microorganism. The coagulation cascades pathway involves many coagulation factors, such as F7, F13A1, FGA, FGB, FGG, KLKB1, KNG1, MASP1, SERPINA1, and SERPIND1. While the DEPs highly expressed in the immature FF participated in protein translation, peptide biosynthetic process, DNA conformation change, and DNA geometric change pathways to facilitate follicle development. The translation pathway contains many ribosomal proteins, such as RPL3, RPL5, RPS3, RPS6, and other translation factors, such as EIF3J, EIF4G2, ETF1, MOV10, and NARS. The DNA conformation change and DNA geometric change involve nine DEPs, DDX1, G3BP1, HMGB1, HMGB2, HMGB3, MCM3, MCM5, MCM6, and RUVBL2. Furthermore, the expressed levels of the main DEPs, C2 and SERPIND1, were confirmed by western blot. Conclusions The differential proteomics revealed the up-regulated DEPs in mature FF take parts in immunoreaction to prevent invasion of microorganisms and the up-regulated DEPs in immature FF participate in protein synthesis, which may improve our knowledge of the follicular microenvironment and its biological roles for reproductive processes in yak. The DEPs, C2 and SERPIND1, can be considered as protein markers for mature yak follicle.

2022 ◽  
Revanth Reddy ◽  
Liwei Yang ◽  
Jesse Liu ◽  
Zhuojie Liu ◽  
Jun Wang

Highly multiplexed analysis of biospecimens significantly advances the understanding of biological basics of diseases, but these techniques are limited by the number of multiplexity and the speed of processing. Here, we present a rapid multiplex method for quantitative detection of protein markers on brain sections with the cellular resolution. This spatial multiplex in situ tagging (MIST) technology is built upon a MIST microarray that contains millions of small microbeads carrying barcoded oligonucleotides. Using antibodies tagged with UV cleavable oligonucleotides, the distribution of protein markers on a tissue slice could be printed on the MIST microarray with high fidelity. The performance of this technology in detection sensitivity, resolution and signal-to-noise level has been fully characterized by detecting brain cell markers. We showcase the codetection of 31 proteins simultaneously within 2 h which is about 10 times faster than the other immunofluorescence-based approaches of similar multiplexity. A full set of computational toolkits was developed to segment the small regions and identify the regional differences across the entire mouse brain. This technique enables us to rapidly and conveniently detect dozens of biomarkers on a tissue specimen, and it can find broad applications in clinical pathology and disease mechanistic studies.

2022 ◽  
Vol 13 (1) ◽  
Tam Vu ◽  
Alexander Vallmitjana ◽  
Joshua Gu ◽  
Kieu La ◽  
Qi Xu ◽  

AbstractMultiplexed mRNA profiling in the spatial context provides new information enabling basic research and clinical applications. Unfortunately, existing spatial transcriptomics methods are limited due to either low multiplexing or complexity. Here, we introduce a spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based decoding. We demonstrate MOSAICA’s multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of five fluorophores with facile error-detection and removal of autofluorescence. MOSAICA’s analysis is strongly correlated with sequencing data (Pearson’s r = 0.96) and was further benchmarked using RNAscopeTM and LGC StellarisTM. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues. We finally demonstrate simultaneous co-detection of protein and mRNA in cancer cells.

2022 ◽  
Brian D Rutter ◽  
Thi-Thu-Huyen Chu ◽  
Kamil K Zajt ◽  
Jean-Felix Dallery ◽  
Richard J O'Connell ◽  

Fungal phytopathogens secrete extracellular vesicles (EVs) associated with enzymes and phytotoxic metabolites. While these vesicles are thought to promote infection, defining the true contents and functions of fungal EVs, as well as suitable protein markers, is an ongoing process. To expand our understanding of fungal EVs and their possible roles during infection, we purified EVs from the hemibiotrophic phytopathogen Colletotrichum higginsianum, the causative agent of anthracnose disease in multiple plant species, including Arabidopsis thaliana. EVs were purified in large numbers from the supernatant of protoplasts but not the supernatant of intact mycelial cultures. We purified two separate populations of EVs, each associated with over 700 detected proteins, including proteins involved in vesicle transport, cell wall biogenesis and the synthesis of secondary metabolites. We selected two SNARE proteins (Snc1 and Sso2) and one 14-3-3 protein (Bmh1) as potential EV markers and generated transgenic lines expressing fluorescent fusions. Each marker was confirmed to be protected inside EVs. Fluorescence microscopy was used to examine the localization of each marker during infection on Arabidopsis leaves. These findings further our understanding of EVs in fungal phytopathogens and will help build an experimental system to study EV inter-kingdom communication between plants and fungi.

2022 ◽  
Vol 12 (1) ◽  
Thangarajan Rajkumar ◽  
Sathyanarayanan Amritha ◽  
Veluswami Sridevi ◽  
Gopisetty Gopal ◽  
Kesavan Sabitha ◽  

AbstractBreast cancer is the most common malignancy among women globally. Development of a reliable plasma biomarker panel might serve as a non-invasive and cost-effective means for population-based screening of the disease. Transcriptomic profiling of breast tumour, paired normal and apparently normal tissues, followed by validation of the shortlisted genes using TaqMan® Low density arrays and Quantitative real-time PCR was performed in South Asian women. Fifteen candidate protein markers and 3 candidate epigenetic markers were validated first in primary breast tumours and then in plasma samples of cases [N = 202 invasive, 16 DCIS] and controls [N = 203 healthy, 37 benign] using antibody array and methylation specific PCR. Diagnostic efficiency of single and combined markers was assessed. Combination of 6 protein markers (Adipsin, Leptin, Syndecan-1, Basic fibroblast growth factor, Interleukin 17B and Dickopff-3) resulted in 65% sensitivity and 80% specificity in detecting breast cancer. Multivariate diagnostic analysis of methylation status of SOSTDC1, DACT2, WIF1 showed 100% sensitivity and up to 91% specificity in discriminating BC from benign and controls. Hence, combination of SOSTDC1, DACT2 and WIF1 was effective in differentiating breast cancer [non-invasive and invasive] from benign diseases of the breast and healthy individuals and could help as a complementary diagnostic tool for breast cancer.

2022 ◽  
Bing-Bing Liu ◽  
Nimaichand Salam ◽  
Manik Prabhu Narsing Rao ◽  
Shuang Cheng ◽  
Yuan-Guo Xie ◽  

Abstract Two extremely halophilic strains, designated SYSU A558-1T and SYSU A121-1, were isolated from a saline sediment sample collected from Aiding salt lake, China. Cells of strains SYSU A558-1T and SYSU A121-1 were Gram-stain-negative, coccoid, and non-motile. The isolates were aerobic and grew at NaCl concentration of 10-30% (optimum, 20-22%), at 20-55ºC (optimum, 37-42ºC) and at pH 6.5-8.5 (optimum, 7.0-8.0). Cells lysed in distilled water. Major polar lipids were phosphatidylglycerol, phosphatidylglycerol phosphate methyl ester, disulphated diglycosyl diether-1 and one unidentified glycolipid. Phylogenetic analyses based on the 16S rRNA gene sequence revealed that the two strains SYSU A558-1T and SYSU A121-1 were closely related to the membranes of the genus Haloterrigena. Phylogenetic trees based on strains SYSU A558-1T and SYSU A121-1 16S rRNA gene sequence, rpoB' gene sequence and concatenation of 87 protein markers demonstrated a robust clade with Haloterrigena turkmenica, Haloterrigena salifodinae and Haloterrigena salina. The genomic DNA G+C contents of strains SYSU A558-1T and SYSU A121-1 were 65.8 and 65.0%, respectively. Phenotypic, chemotaxonomic characteristics and phylogenetic properties suggested that the two strains SYSU A558-1T and SYSU A121-1 represent a novel species of the genus Haloterrigena, for which the name Haloterrigena gelatinilytica sp. nov. is proposed. The type strain is SYSU A558-1T (= KCTC 4259T = CGMCC 1.15953T).

2022 ◽  
Vol 23 (1) ◽  
Haitao Tu ◽  
Zhi Wei Zhang ◽  
Lifeng Qiu ◽  
Yuning Lin ◽  
Mei Jiang ◽  

Abstract Background Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) are common age-related neurodegenerative diseases comprising Lewy body spectrum disorders associated with cortical and subcortical Lewy body pathology. Over 30% of PD patients develop PD dementia (PDD), which describes dementia arising in the context of established idiopathic PD. Furthermore, Lewy bodies frequently accompany the amyloid plaque and neurofibrillary tangle pathology of Alzheimer’s disease (AD), where they are observed in the amygdala of approximately 60% of sporadic and familial AD. While PDD and DLB share similar pathological substrates, they differ in the temporal onset of motor and cognitive symptoms; however, protein markers to distinguish them are still lacking. Methods Here, we systematically studied a series of AD and PD pathogenesis markers, as well as mitochondria, mitophagy, and neuroinflammation-related indicators, in the substantia nigra (SN), temporal cortex (TC), and caudate and putamen (CP) regions of human post-mortem brain samples from individuals with PDD and DLB and condition-matched controls. Results We found that p-APPT668 (TC), α-synuclein (CP), and LC3II (CP) are all increased while the tyrosine hydroxylase (TH) (CP) is decreased in both PDD and DLB compared to control. Also, the levels of Aβ42 and DD2R, IBA1, and p-LRRK2S935 are all elevated in PDD compared to control. Interestingly, protein levels of p-TauS199/202 in CP and DD2R, DRP1, and VPS35 in TC are all increased in PDD compared to DLB. Conclusions Together, our comprehensive and systematic study identified a set of signature proteins that will help to understand the pathology and etiology of PDD and DLB at the molecular level.

2022 ◽  
Vol 12 ◽  
Zicheng Hu ◽  
Sanchita Bhattacharya ◽  
Atul J. Butte

Modern cytometry technologies present opportunities to profile the immune system at a single-cell resolution with more than 50 protein markers, and have been widely used in both research and clinical settings. The number of publicly available cytometry datasets is growing. However, the analysis of cytometry data remains a bottleneck due to its high dimensionality, large cell numbers, and heterogeneity between datasets. Machine learning techniques are well suited to analyze complex cytometry data and have been used in multiple facets of cytometry data analysis, including dimensionality reduction, cell population identification, and sample classification. Here, we review the existing machine learning applications for analyzing cytometry data and highlight the importance of publicly available cytometry data that enable researchers to develop and validate machine learning methods.

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