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Abstract Background Cultivated peanut (Arachis hypogaea, AABB genome), an allotetraploid from a cross between A. duranensis (AA genome) and A. ipaensis (BB genome), is an important oil and protein crop with released genome and RNA-seq sequence datasets. These datasets provide the molecular foundation for studying gene expression and evolutionary patterns. However, there are no reports on the proteomic data of A. hypogaea cv. Tifrunner, which limits understanding of its gene function and protein level evolution. Results This study sequenced the A. hypogaea cv. Tifrunner leaf and root proteome using the tandem mass tag technology. A total of 4803 abundant proteins were identified. The 364 differentially abundant proteins were estimated by comparing protein abundances between leaf and root proteomes. The differentially abundant proteins enriched the photosystem process. The number of biased abundant homeologs between the two sub-genomes A (87 homeologs in leaf and root) and B (69 and 68 homeologs in leaf and root, respectively) was not significantly different. However, homeologous proteins with biased abundances in different sub-genomes enriched different biological processes. In the leaf, homeologs biased to sub-genome A enriched biosynthetic and metabolic process, while homeologs biased to sub-genome B enriched iron ion homeostasis process. In the root, homeologs with biased abundance in sub-genome A enriched inorganic biosynthesis and metabolism process, while homeologs with biased abundance in sub-genome B enriched organic biosynthesis and metabolism process. Purifying selection mainly acted on paralogs and homeologs. The selective pressure values were negatively correlated with paralogous protein abundance. About 77.42% (24/31) homeologous and 80% (48/60) paralogous protein pairs had asymmetric abundance, and several protein pairs had conserved abundances in the leaf and root tissues. Conclusions This study sequenced the proteome of A. hypogaea cv. Tifrunner using the leaf and root tissues. Differentially abundant proteins were identified, and revealed functions. Paralog abundance divergence and homeolog bias abundance was elucidated. These results indicate that divergent abundance caused retention of homologs in A. hypogaea cv. Tifrunner.

Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer’s disease. In this study, the tear proteome profile of patients with idiopathic PD (iPD, n = 24), carriers of the E46K-SNCA mutation (n = 3) and healthy control (CT, n = 27) subjects was analyzed to identify candidate biomarkers for the diagnosis of PD. An observational, prospective and case-control pilot study was carried out, analyzing the participants tear samples by nano-liquid chromatography–mass spectrometry (nLC–MS/MS) and assessing their neurological impairment. The proteomic data obtained are available at ProteomeXchange with identifier 10.6019/PXD028811. These analyses led to the identification of 560 tear proteins, some of which were deregulated in PD patients and that have been implicated in immune responses, inflammation, apoptosis, collagen degradation, protein synthesis, defense, lipid transport and altered lysosomal function. Of these proteins, six were related to neurodegenerative processes and showed a good capacity to classify patients and controls. These findings revealed that certain proteins were upregulated in the tears of PD patients, mainly proteins involved in lysosomal function. Thus, in this study, tear proteins were identified that are implicated in neurodegeneration and that may be related to an aggressive disease phenotype in PD patients.

Inhibiting β-amyloid (Aβ) aggregation is of significance in finding potential candidates for Alzheimer’s disease (AD) treatment. Accumulating evidence suggests that nutrition is important for improving cognition and reducing AD risk. Walnut has been widely used as a functional food for brain health; however the underlying mechanisms remain unknown. Here, we investigated the molecular level alteration in Arctic mutant Aβ42 induced aggregation cell model by RNA-seq and iTRAQ approaches after walnut-derived peptides Pro-Pro-Lys-Asn-Trp (PW5) and Trp-Pro-Pro-Lys-Asn (WN5) interventions. PW5 or WN5 could significantly decrease abnormal Aβ42 aggregates. However, resultant alterations in transcriptome (substantially unchanged) were inconsistent with proteomic data (marked change). Proteomic analysis revealed 184 and 194 differentially expressed proteins unique to PW5 and WN5 treatment, respectively, for inhibiting Aβ42 protein production or increasing protein degradation via the mismatch repair pathways. Our study provides new insights into the effectiveness of food-derived peptides for anti-Aβ42 aggregation in AD.

Background: Proteome profile changes post-severe acute respiratory syndrome coronavirus 2 (post-SARS-CoV-2) infection in different body sites of humans remains an active scientific investigation whose solutions stand a chance of providing more information on what constitutes SARS-CoV-2 pathogenesis. While proteomics has been used to understand SARS-CoV-2 pathogenesis, there are limited data about the status of proteome profile in different human body sites infected by sarscov2 virus. To bridge this gap, our study aims to profile the proteins secreted in urine, bronchoalveolar lavage fluid (BALF), gargle solution, and nasopharyngeal samples and assess the proteome differences in these body samples collected from SARS-CoV-2-positive patients. Materials and methods: We downloaded publicly available proteomic data from (https://www.ebi.ac.uk/pride/). The data we downloaded had the following identifiers: i) PXD019423, n=3 from Charles Tanford Protein Center in Germany. ii) PXD018970, n=15 from Beijing Proteome Research Centre, China. iii)PXD022085, n=5 from Huazhong University of Science and Technology, China, and iv) PXD022889, n=18 from Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA. MaxQuant was used for the peptide spectral matching using human and SARS-CoV-2 downloaded from UniProt database (access date 13th October 2021). Results: The individuals infected with SARS-CoV-2 viruses displayed a different proteome diversity from the different body sites we investigated. Overally, we identified 1809 proteins across the four different sample types we compared. Urine and BALF samples had significantly more abundant SARS-CoV-2 proteins than the other body sites we compared. Urine samples had 257(33.7%) unique proteins followed by nasopharyngeal with 250(32.8%) unique proteins. Garlge solution and BALF had 38(5%) and 73(9.6%) unique proteins respectively. Conclusions: Urine, gargle solution, nasopharyngeal, and bronchoalveolar lavage fluid samples have different protein diversity in individuals infected with SARS-CoV-2. Moreover, our data also demonstrated that a given body site is characterized by a unique set of proteins in SARS-CoV-2 seropositive individuals. Key words: SARS-CoV-2, body sites,urine,gargle solution, BALF,nasopharyngeal

In fungi, metals are associated with the expression of virulence factors. However, it is unclear whether the uptake of metals affects their pathogenicity. This study aimed to evaluate the effect of iron/copper in modulating pathogenicity and proteomic response in two clinical isolates of C. neoformans with high and low pathogenicity. Methods: In both isolates, the effect of 50 µM iron and 500 µM copper on pathogenicity, capsule induction, and melanin production was evaluated. We then performed a quantitative proteomic analysis of cytoplasmic extracts exposed to that combination. Finally, the effect on pathogenicity by iron and copper was evaluated in eight additional isolates. Results: In both isolates, the combination of iron and copper increased pathogenicity, capsule size, and melanin production. Regarding proteomic data, proteins with increased levels after iron and copper exposure were related to biological processes such as cell stress, vesicular traffic (Ap1, Vps35), cell wall structure (Och1, Ccr4, Gsk3), melanin biosynthesis (Hem15, Mln2), DNA repair (Chk1), protein transport (Mms2), SUMOylation (Uba2), and mitochondrial transport (Atm1). Increased pathogenicity by exposure to metal combination was also confirmed in 90% of the eight isolates. Conclusions: The combination of these metals enhances pathogenicity and increases the abundance of proteins related to the main virulence factors.

Coral health is currently diagnosed retroactively; colonies are deemed “stressed” upon succumbing to bleaching or disease. Ideally, health inferences would instead be made on a pre-death timescale that would enable, for instance, environmental mitigation that could promote coral resilience. To this end, diverse Caribbean coral (Orbicella faveolata) genotypes of varying resilience to high temperatures along the Florida Reef Tract were exposed herein to elevated temperatures in the laboratory, and a proteomic analysis was taken with a subset of 20 samples via iTRAQ labeling followed by nano-liquid chromatography + mass spectrometry; 46 host coral and 40 Symbiodiniaceae dinoflagellate proteins passed all stringent quality control criteria, and the partial proteomes of biopsies of (1) healthy controls, (2) sub-lethally stressed samples, and (3) actively bleaching corals differed significantly from one another. The proteomic data were then used to train predictive models of coral colony bleaching susceptibility, and both generalized regression and machine-learning-based neural networks were capable of accurately forecasting the bleaching susceptibility of coral samples based on their protein signatures. Successful future testing of the predictive power of these models in situ could establish the capacity to proactively monitor coral health.

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, mRNA transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex. To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns. Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575), while most of the investigated target receptors showed low or negative correlations. The high variability in the correspondence of mRNA expression and receptor warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This highlights the longstanding value of molecular imaging data and the need for comprehensive proteomic data.

Aneuploidy, a state of chromosome imbalance, is a hallmark of human tumors, but its role in cancer still remains to be fully elucidated. To understand the consequences of whole chromosome-level aneuploidies on the proteome, we integrated aneuploidy, transcriptomic and proteomic data from hundreds of TCGA/CPTAC tumor samples. We found a surprisingly large number of expression changes happened on other, non-aneuploid chromosomes. Moreover, we identified an association between those changes and co-complex members of proteins from aneuploid chromosomes. This co-abundance association is tightly regulated for aggregation-prone aneuploid proteins and those involved in a smaller number of complexes. On the other hand, we observe that complexes of the cellular core machinery are under functional selection to maintain their stoichiometric balance in aneuploid tumors. Ultimately, we provide evidence that those compensatory and functional maintenance mechanisms are established through post-transcriptional control and that the degree of success of a tumor to deal with aneuploidy-induced stoichiometric imbalance impacts the activation of cellular protein degradation programs and patient survival.

Abstract Background Cryptosporidium andersoni initiates infection by releasing sporozoites from oocysts through excystation. However, the proteins involved in excystation are unknown. Determining the proteins that participate in the excystation of C. andersoni oocysts will increase our understanding of the excystation process. Methods Cryptosporidium andersoni oocysts were collected and purified from the feces of naturally infected adult cows. Tandem mass tags (TMT), coupled with liquid chromatography–tandem mass spectrometry (LC–MS/MS) proteomic analysis, were used to investigate the proteomic expression profiles of C. andersoni oocysts before and after excystation. Results Proteomic analysis identified a total of 1586 proteins, of which 17 were differentially expressed proteins (DEPs) upon excystation. These included 10 upregulated and seven downregulated proteins. The 17 proteins had multiple biological functions associated with control of gene expression at the level of transcription and biosynthetic and metabolic processes. Quantitative real-time RT-PCR of eight selected genes validated the proteomic data. Conclusions This study provides information on the protein composition of C. andersoni oocysts as well as possible excystation factors. The data may be useful in identifying genes for diagnosis, vaccine development, and immunotherapy for Cryptosporidium. Graphical Abstract