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In recent years, high-throughput technologies have contributed to the development of a more precise picture of the human proteome. However, 2129 proteins remain listed as missing proteins (MPs) in the newest neXtProt release (2019-02). The main reasons for MPs are a low abundance, a low molecular weight, unexpected modifications, membrane characteristics, and so on. Moreover, >50% of the MS/MS data have not been successfully identified in shotgun proteomics. Open-pFind, an efficient open search engine, recently released by the pFind group in China, might provide an opportunity to identify these buried MPs in complex samples. In this study, proteins and potential MPs were identified using Open-pFind and three other search engines to compare their performance and efficiency with three large-scale data sets digested by three enzymes (Glu-C, Lys-C, and trypsin) with specificity on different amino acid (AA) residues. Our results demonstrated that Open-pFind identified 44.7−93.1% more peptide-spectrum matches and 21.3−61.6% more peptide sequences than the secondbest search engine. As a result, Open-pFind detected 53.1% more MP candidates than MaxQuant and 8.8% more candidate MPs than Proteome Discoverer. In total, 5 (PE2) of the 124 MP candidates identified by Open-pFind were verified with 2 or 3 unique peptides containing more than 9 AAs by using a spectrum theoretical prediction with pDeep and synthesized peptide matching with pBuild after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant filtering. These five verified MPs can be saved as PE1 proteins. In addition, three other MP candidates were verified with two unique peptides (one peptide containing more than 9 AAs and the other containing only 8 AAs), which was slightly lower than the criteria listed by C-HPP and required additional verification information. More importantly, unexpected modifications were detected in these MPs. All MS data sets have been deposited into ProteomeXchange with the identifier PXD015759.

Confined experiments are carried out to simulate the closed environment of space capsule on the ground. The Chinese Controlled Ecological Life Support System (CELSS) is designed including a closed-loop system supporting 4 healthy volunteers surviving for 180 days, and we aim to reveal the temporal characteristics of the oropharyngeal and nasal microbiota structure in crewmembers stayed 180 days in the CELSS, so as to accumulate the information about microbiota balance associated with respiratory health for estimating health risk in future spaceflight. We investigated the distribution of microorganisms and their dynamic characteristics in the nasal cavity and oropharynx of occupants with prolonged confinement. Based on the 16S rDNA v3–v4 regions using Illumina high-throughput sequencing technology, the oropharyngeal and nasal microbiota were monitored at eight time points during confinement. There were significant differences between oropharyngeal and nasal microbiota, and there were also individual differences among the same site of different volunteers. Analysis on the structure of the microbiota showed that, in the phylum taxon, the nasal bacteria mainly belonged to Actinobacteria, Firmicutes, Proteobacteria, Bacteroidetes, etc. In addition to the above phyla, in oropharyngeal bacteria Fusobacterial accounted for a relatively high proportion. In the genus taxon, the nasal and oropharyngeal bacteria were independent. Corynebacterium and Staphylococcus were dominant in nasal cavity, and Corynebacterium, Streptococcus, and Neisseria were dominant in oropharynx. With the extension of the confinement time, the abundance of Staphylococcus in the nasal cavity and Neisseria in the oropharynx increased, and the index Chao fluctuated greatly from 30 to 90 days after the volunteers entered the CELSS.Conclusion: The structure and diversity of the nasal and oropharyngeal microbiota changed in the CELSS, and there was the phenomenon of migration between occupants, suggesting that the microbiota structure and health of the respiratory tract could be affected by living in a closed environment for a long time.

Fungal natural products play a prominent role in the development of pharmaceuticalagents. Two new cyclic tetrapeptides (CTPs), westertide A (1) and B (2), with eight known compounds (3–10) were isolated from the fungus Aspergillus westerdijkiae guided by OSMAC (one strain-many compounds) and molecular networking strategies. The structures of new compounds were unambiguously determined by a combination of NMR and mass data analysis, and chemical methods. All of the isolates were evaluated for antimicrobial effects, synergistic antifungal activity, cytotoxic activity, and HDAC inhibitory activity. Compounds 1–2 showed synergistic antifungal activity against Candida albicans SC5314 with the presence of rapamycin and weak HDAC (histone deacetylase) inhibitory activity. These results indicate that molecular networking is an efficient approach for dereplication and identification of new CTPs. CTPs might be a good starting point for the development of synergistic antifungal agents.

Deinococcus radiodurans is a robust bacterium best known for its capacity to resist to radiation. In this study, the SDS-PAGE coupled with high-precision LC-MS/MS was used to study the D. radiodurans proteome. A total of 1951 proteins were identified which covers 63.18% protein-coding genes. Comparison of the identified proteins to the key enzymes in amino acid biosyntheses from KEGG database showed the methionine biosynthesis module is incomplete while other amino acid biosynthesis modules are complete, which indicated methionine auxotrophy in D. radiodurans. The subsequent amino acid-auxotrophic screening has verified methionine instead of other amino acids is essential for the growth of D. radiodurans. With molecular evolutionary genetic analysis, we found the divergence in methionine biosynthesis during the evolution of the common ancestor of bacteria. We also found D. radiodurans lost the power of synthesizing methionine because of the missing metA and metX in two types of methionine biosyntheses. For the first time, this study used high-coverage proteome analysis to identify D. radiodurans amino acid auxotrophy, which provides the important reference for the development of quantitative proteomics analysis using stable isotope labeling in metabolomics of D. radiodurans and in-depth analysis of the molecular mechanism of radiation resistance.