Routine Workflow of Spatial Proteomics on Micro-formalin-Fixed Paraffin-Embedded Tissues.

In the era of single-cell biology, spatial proteomics has emerged as an important frontier. However, it still faces several challenges in technology. Formalin-fixed paraffin-embedded (FFPE) tissues are an important material in spatial proteomics, in which fixed tissues are excised using laser capture microdissection (LCM), followed by protein identification with mass spectrometry. For a satisfied spatial proteomics upon FFPE tissues, the excision area is expected to be as small as possible, and the identified proteins are countered upon as much as possible. For a general laboratory for spatial proteomics, a routine workflow is required, not relying on any special device, and is easily operating. In view of these challenges in technology, we initiated a technology evaluation throughout the entire procedure of proteomic analysis with micro-FFPE tissues. In contrast to the protocols reported previously, several innovations in technology were proposed and conducted, such as removal of destaining, decross-linking with "hang-down", solution simplification for peptide generation and balancing to excision area, and capture rate of micro-FFPE tissues. After optimization of all the necessary steps, a routine workflow was established, in which the minimized area for protein identification was 0.002 mm2, while the excision area for a consistent proteomic analysis was 0.05 mm2. Using the developed workflow and collecting the micro-FFPE tissues continuously, for the first time, a spatial proteomic atlas of mouse brain was preliminarily constructed, which exhibited the typical characteristics of spatial-dependent protein abundance and functional enrichment.

New Set of Isobaric Labeling Reagents for Quantitative 16Plex Proteomics.

Peptide labeling by isobaric tags is a powerful approach for the relative quantitative analysis of proteomes in multiple groups. There has been a revolution in the innovation of new isobaric reagents; however, great effort is being made to expand simultaneous labeling groups to identify more labeled peptides and reduce reporter ion signal suppression. We redesigned the original chemical structure of the deuterium isobaric amine-reactive tag developed in our laboratory. We optimized the synthetic pathway to create a new set of 16-plex isobaric tags (IBT-16plex). The novel reagent enabled almost complete labeling of peptides within 90 min, with all labeling reporter ions exhibiting comparable MS/MS signals. Compared to a typical 16plex reagent, TMTpro-16plex, the peptides and proteins identified by IBT-16plex in trypsinized HeLa cells were significantly increased by 14.8 and 8.6%, respectively. Moreover, differences in peptide abundance within 10-fold among multiple groups were barely suppressed in IBT-16plex, whereas the dynamic range in TMTpro-16plex-labeled groups was smaller. After quantitative examination of MCF7 cell proteins, IBT-16plex was confirmed as feasible and useful for evaluating protein responses of glucose-starved MCF7 cells to a glucose-rich medium.

Prediction and Validation of Mouse Meiosis-Essential Genes Based on Spermatogenesis Proteome Dynamics.

The molecular mechanism associated with mammalian meiosis has yet to be fully explored, and one of the main reasons for this lack of exploration is that some meiosis-essential genes are still unknown. The profiling of gene expression during spermatogenesis has been performed in previous studies, yet few studies have aimed to find new functional genes. Since there is a huge gap between the number of genes that are able to be quantified and the number of genes that can be characterized by phenotype screening in one assay, an efficient method to rank quantified genes according to phenotypic relevance is of great importance. We proposed to rank genes by the probability of their function in mammalian meiosis based on global protein abundance using machine learning. Here, nine types of germ cells focusing on continual substages of meiosis prophase I were isolated, and the corresponding proteomes were quantified by high-resolution MS. By combining meiotic labels annotated from the mouse genomics informatics mouse knockout database and the spermatogenesis proteomics dataset, a supervised machine learning package, FuncProFinder (https://github.com/sjq111/FuncProFinder), was developed to rank meiosis-essential candidates. Of the candidates whose functions were unannotated, four of 10 genes with the top prediction scores, Zcwpw1, Tesmin, 1700102P08Rik, and Kctd19, were validated as meiosis-essential genes by knockout mouse models. Therefore, mammalian meiosis-essential genes could be efficiently predicted based on the protein abundance dataset, which provides a paradigm for other functional gene mining from a related abundance dataset.

Dynamic Responses of Chromosome-Binding Protein Complexes to Meiotic Prophase I of Mouse Spermatocyte.

Meiotic prophase I (MPI) is the most important event in mammalian meiosis. The status of the chromosome-binding proteins (CBPs) and the corresponding complexes and their functions in MPI have not yet been well scrutinized. Quantitative proteomics focused on MPI-related CBPs was accomplished, in which mouse primary spermatocytes in four different subphases of MPI were collected, and chromosome-enriched proteins were extracted and quantitatively identified. According to a stringent criterion, 1136 CBPs in the MPI subphases were quantified. Looking at the dynamic patterns of CBP abundance in response to MPI progression, the patterns were broadly divided into two groups: high abundance in leptotene and zygotene or that in pachytene and diplotene. Furthermore, 152 such CBPs were regarded as 26 CBP complexes with strict filtration, in which some of these complexes were perceived to be MPI-dependent for the first time. These complexes basically belonged to four functional categories, while their dynamic abundance changes following MPI appeared; the functions of DNA replication decreased; and transcription and synapsis were activated in zygotene, pachytene, and diplotene; in contrast to the traditional prediction, condensin activity weakened in pachytene and diplotene. Profiling of protein complexes thus offered convincing evidence of the importance of CBP complexes in MPI.

Quantitative Evaluation of Serum Proteins Uncovers a Protein Signature Related to Maturity-Onset Diabetes of the Young (MODY).

Maturity-onset diabetes of the young (MODY) is an inherited monogenic type of diabetes. Genetic mutations in MODY often cause nonsynonymous changes that directly lead to the functional distortion of proteins and the pathological consequences. Herein, we proposed that the inherited mutations found in a MODY family could cause a disturbance of protein abundance, specifically in serum. The serum samples were collected from a Uyghur MODY family through three generations, and the serum proteins after depletion treatment were examined by quantitative proteomics to characterize the MODY-related serum proteins followed by verification using target quantification of proteomics. A total of 32 serum proteins were preliminarily identified as the MODY-related. Further verification test toward the individual samples demonstrated the 12 candidates with the significantly different abundance in the MODY patients. A comparison of the 12 proteins among the sera of type 1 diabetes, type 2 diabetes, MODY, and healthy subjects was conducted and revealed a protein signature related with MODY composed of the serum proteins such as SERPINA7, APOC4, LPA, C6, and F5.

Tissue-Based Proteogenomics Reveals that Human Testis Endows Plentiful Missing Proteins.

Investigations of missing proteins (MPs) are being endorsed by many bioanalytical strategies. We proposed that proteogenomics of testis tissue was a feasible approach to identify more MPs because testis tissues have higher gene expression levels. Here we combined proteomics and transcriptomics to survey gene expression in human testis tissues from three post-mortem individuals. Proteins were extracted and separated with glycine- and tricine-SDS-PAGE. A total of 9597 protein groups were identified; of these, 166 protein groups were listed as MPs, including 138 groups (83.1%) with transcriptional evidence. A total of 2948 proteins are designated as MPs, and 5.6% of these were identified in this study. The high incidence of MPs in testis tissue indicates that this is a rich resource for MPs. Functional category analysis revealed that the biological processes that testis MPs are mainly involved in are sexual reproduction and spermatogenesis. Some of the MPs are potentially involved in tumorgenesis in other tissues. Therefore, this proteogenomics analysis of individual testis tissues provides convincing evidence of the discovery of MPs. All mass spectrometry data from this study have been deposited in the ProteomeXchange (data set identifier PXD002179).

Associations of Triglycerides/High-Density Lipoprotein Cholesterol Ratio With Insulin Resistance, Impaired Glucose Tolerance, and Diabetes in American Adults at Different Vitamin D3 Levels.

Background: Previous studies have shown that vitamin D3 (VD3) may be a protective factor for diabetes mellitus (DM), while triglycerides/high-density lipoprotein (TG/HDL) may be a risk factor for diabetes. However, no existing study has elucidated the interaction between TG/HDL and VD3. Therefore, this work aimed to investigate the relationships of TG/HDL with insulin resistance (IR), impaired glucose tolerance (IGT), and DM at different VD3 levels. Methods: With the use of the data from five National Health and Nutrition Examination Survey (NHANES) cycles, a total of 2,929 males and 3,031 females were divided into 4 groups according to their VD3 levels. Logistic regression was performed to observe the associations of TG/HDL ratio with IR, IGT, and DM in different groups. Results: The relationships of TG/HDL with IR, IGT, and DM showed a threshold effect, with the cutoff values of 1.094, 1.51, and 1.11, respectively. On both sides of the cutoff values, the correlation was first weakened and then enhanced with the increase in VD3 levels. Conclusion: TG/HDL is a risk factor for IR, IGT, and DM. Both too low and too high levels of VD3 can strengthen this association, whereas keeping VD3 at a reasonable level helps to reduce the associations of TG/HDL with IR, IGT, and DM.