Hidden proteome of synaptic vesicles in the mammalian brain.

Current proteomic studies clarified canonical synaptic proteins that are common to many types of synapses. However, proteins of diversified functions in a subset of synapses are largely hidden because of their low abundance or structural similarities to abundant proteins. To overcome this limitation, we have developed an "ultra-definition" (UD) subcellular proteomic workflow. Using purified synaptic vesicle (SV) fraction from rat brain, we identified 1,466 proteins, three times more than reported previously. This refined proteome includes all canonical SV proteins, as well as numerous proteins of low abundance, many of which were hitherto undetected. Comparison of UD quantifications between SV and synaptosomal fractions has enabled us to distinguish SV-resident proteins from potential SV-visitor proteins. We found 134 SV residents, of which 86 are present in an average copy number per SV of less than one, including vesicular transporters of nonubiquitous neurotransmitters in the brain. We provide a fully annotated resource of all categorized SV-resident and potential SV-visitor proteins, which can be utilized to drive novel functional studies, as we characterized here Aak1 as a regulator of synaptic transmission. Moreover, proteins in the SV fraction are associated with more than 200 distinct brain diseases. Remarkably, a majority of these proteins was found in the low-abundance proteome range, highlighting its pathological significance. Our deep SV proteome will provide a fundamental resource for a variety of future investigations on the function of synapses in health and disease.

Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection.

Discovery of variant peptides such as a single amino acid variant (SAAV) in shotgun proteomics data is essential for personalized proteomics. Both the resolution of shotgun proteomics methods and the search engines have improved dramatically, allowing for confident identification of SAAV peptides. However, it is not yet known if these methods are truly successful in accurately identifying SAAV peptides without prior genomic information in the search database. We studied this in unprecedented detail by exploiting publicly available long-read RNA sequences and shotgun proteomics data from the gold standard reference cell line NA12878. Searching spectra from this cell line with the state-of-the-art open modification search engine ionbot against carefully curated search databases resulted in 96.7% false-positive SAAVs and an 85% lower true positive rate than searching with peptide search databases that incorporate prior genetic information. While adding genetic variants to the search database remains indispensable for correct peptide identification, inclusion of long-read RNA sequences in the search database contributes only 0.3% new peptide identifications. These findings reveal the differences in SAAV detection that result from various approaches, providing guidance to researchers studying SAAV peptides and developers of peptide spectrum identification tools.

Optimization of Data-Independent Acquisition Mass Spectrometry for Deep and Highly Sensitive Proteomic Analysis.

Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteomic analysis overtop the existing data-dependent acquisition (DDA)-MS-based proteomic analysis to enable deep proteome coverage and precise relative quantitative analysis in single-shot liquid chromatography (LC)-MS/MS. However, DIA-MS-based proteomic analysis has not yet been optimized in terms of system robustness and throughput, particularly for its practical applications. We established a single-shot LC-MS/MS system with an MS measurement time of 90 min for a highly sensitive and deep proteomic analysis by optimizing the conditions of DIA and nanoLC. We identified 7020 and 4068 proteins from 200 ng and 10 ng, respectively, of tryptic floating human embryonic kidney cells 293 (HEK293F) cell digest by performing the constructed LC-MS method with a protein sequence database search. The numbers of identified proteins from 200 ng and 10 ng of tryptic HEK293F increased to 8509 and 5706, respectively, by searching the chromatogram library created by gas-phase fractionated DIA. Moreover, DIA protein quantification was highly reproducible, with median coefficients of variation of 4.3% in eight replicate analyses. We could demonstrate the power of this system by applying the proteomic analysis to detect subtle changes in protein profiles between cerebrums in germ-free and specific pathogen-free mice, which successfully showed that >40 proteins were differentially produced between the cerebrums in the presence or absence of bacteria.

A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training.

The skeletal muscle proteome alterations to aging and resistance training have been reported in prior studies. However, conventional proteomics in skeletal muscle typically yields wide protein abundance ranges that mask the detection of lowly expressed proteins. Thus, we adopted a novel deep proteomics approach whereby myofibril (MyoF) and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS). Specifically, we investigated MyoF and non-MyoF proteomic profiles of the vastus lateralis muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6). Additionally, MA muscle was analyzed following eight weeks of resistance training (RT, 2d/week). Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888-5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944-3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteomes were evident between age cohorts, and most differentially expressed non-MyoF proteins (447/543) were more enriched in MA versus Y. Biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. RT in MA participants only altered ~0.3% of MyoF and ~1.0% of non-MyoF proteomes. In summary, aging and RT predominantly affect non-contractile proteins in skeletal muscle. Additionally, marginal proteome adaptations with RT suggest more rigorous training may stimulate more robust effects or that RT, regardless of age, subtly alters basal state skeletal muscle protein abundances.

Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer.

The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.

A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training.

We examined the myofibrillar (MyoF) and non-myofibrillar (non-MyoF) proteomic profiles of the vastus lateralis (VL) muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6), and MA following eight weeks of knee extensor resistance training (RT, 2d/week). Shotgun/bottom-up proteomics in skeletal muscle typically yields wide protein abundance ranges that mask lowly expressed proteins. Thus, we adopted a novel approach whereby the MyoF and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS) analysis. A total of 10,866 proteins (4,421 MyoF and 6,445 non-MyoF) were identified. Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888-5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944-3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteome were evident between age cohorts. Further, most of these age-related non-MyoF proteins (447/543) were more enriched in MA versus Y. Several biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including (but not limited to) increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. Non-MyoF proteins associated with splicing and proteostasis were further interrogated, and in agreement with bioinformatics, alternative protein variants, spliceosome-associated proteins (snRNPs), and proteolysis-related targets were more abundant in MA versus Y. RT in MA non-significantly increased VL muscle cross-sectional area (+6.5%, p=0.066) and significantly increased knee extensor strength (+8.7%, p=0.048). However, RT modestly altered the MyoF (~0.3%, 11 upregulated and two downregulated proteins) and non-MyoF proteomes (~1.0%, 56 upregulated and eight downregulated proteins, p<0.01). Further, RT did not affect predicted biological processes in either fraction. Although participant numbers were limited, these preliminary results using a novel deep proteomic approach in skeletal muscle suggest that aging and RT predominantly affects protein abundances in the non-contractile protein pool. However, the marginal proteome adaptations occurring with RT suggest either: a) this may be an aging-associated phenomenon, b) more rigorous RT may stimulate more robust effects, or c) RT, regardless of age, subtly affects skeletal muscle protein abundances in the basal state.

Fritted tip capillary column with negligible dead volume facilitated ultrasensitive and deep proteomics.

Insufficient chromatographic performance results in reduced utilization of MS/MS scan capacity of advanced MS instruments. Improvement in peptide separation in liquid chromatography is critical for increasing the sensitivity and quantification performance of LC-MS-based proteomics. However, existing column fabrication methods suffer from slow packing, large dead volume, and band broadening. Herein, we reported that directly pulling emitter tips within short frits after fast packing (termed "filled tip") can minimize the dead volume, improving ionization efficiency and reducing band broadening. Within 10 min, our method can pack over 10 cm for 50 µm I.D. capillary columns under 6-8 MPa and over 50 cm for 75 µm I.D. long capillary columns under 70 MPa. We can identify an average of 3043 protein groups and 33 309 peptide-spectrum matches (PSMs) from 1 ng of HeLa digest using a 50 µm I.D. x 20 cm "filled tip" column, with good reproducibility. The number of protein groups increased by 50% and 96% when compared with a 50 µm I.D. "void tip" column and a 100 µm I.D. column with a manually pulled tip, respectively. We identified an average of 5534 protein groups and 71 769 PSMs from 10 ng of HeLa digest. In addition, using 75 µm I.D. x 50 cm "filled tip" columns, we can identify on average 8829 protein groups and 170 751 PSMs in single-shot data-dependent acquisition analysis from 500 ng of 293T digested peptides. Importantly, good repeatability and reproducibility of "filled tip" method were verified by results from columns fabricated in three batches and by different persons. When compared with conventional columns with "void tips", "filled tip" columns reduced median full peak widths by 19% and alleviated sampling redundancy by 10%. Collectively, we developed an easy-to-use, versatile and robust column fabrication method for both narrow-bore and long capillary columns, which achieved great sensitivity and depth in proteomic analysis.

Reshaping of the Arabidopsis thaliana Proteome Landscape and Co-regulation of Proteins in Development and Immunity.

Proteome remodeling is a fundamental adaptive response, and proteins in complexes and functionally related proteins are often co-expressed. Using a deep sampling strategy we define core proteomes of Arabidopsis thaliana tissues with around 10 000 proteins per tissue, and absolutely quantify (copy numbers per cell) nearly 16 000 proteins throughout the plant lifecycle. A proteome-wide survey of global post-translational modification revealed amino acid exchanges pointing to potential conservation of translational infidelity in eukaryotes. Correlation analysis of protein abundance uncovered potentially new tissue- and age-specific roles of entire signaling modules regulating transcription in photosynthesis, seed development, and senescence and abscission. Among others, the data suggest a potential function of RD26 and other NAC transcription factors in seed development related to desiccation tolerance as well as a possible function of cysteine-rich receptor-like kinases (CRKs) as ROS sensors in senescence. All of the components of ribosome biogenesis factor (RBF) complexes were found to be co-expressed in a tissue- and age-specific manner, indicating functional promiscuity in the assembly of these less-studied protein complexes in Arabidopsis.Furthermore, we characterized detailed proteome remodeling in basal immunity by treating Arabidopsis seeldings with flg22. Through simultaneously monitoring phytohormone and transcript changes upon flg22 treatment, we obtained strong evidence of suppression of jasmonate (JA) and JA-isoleucine (JA-Ile) levels by deconjugation and hydroxylation by IAA-ALA RESISTANT3 (IAR3) and JASMONATE-INDUCED OXYGENASE 2 (JOX2), respectively, under the control of JASMONATE INSENSITIVE 1 (MYC2), suggesting an unrecognized role of a new JA regulatory switch in pattern-triggered immunity. Taken together, the datasets generated in this study present extensive coverage of the Arabidopsis proteome in various biological scenarios, providing a rich resource available to the whole plant science community.