UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow.

We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high-quality tandem mass spectra (MS2) from 0.8 million unique peptide ions, UniSpec learned with a peptide fragmentation dictionary encompassing 7919 fragment peaks. Among these, 5712 are neutral loss peaks, with 2310 corresponding to modification-specific neutral losses. Remarkably, UniSpec can predict 73%-77% of fragment intensities based on our NIST reference library spectra, a significant leap from the 35%-45% coverage of only b and y ions. Comparative studies with Prosit elucidate that while both models are strong at predicting their respective fragment ion series, UniSpec particularly shines in generating more complex MS2 spectra with diverse ion annotations. The integration of UniSpec's predictions into shotgun proteomics data analysis boosts the identification rate of tryptic peptides by 48% at a 1% false discovery rate (FDR) and 60% at a more confident 0.1% FDR. Using UniSpec's predicted in-silico spectral library, the search results closely matched those from search engines and experimental spectral libraries used in peptide identification, highlighting its potential as a stand-alone identification tool. The source code and Python scripts are available on GitHub (https://github.com/usnistgov/UniSpec) and Zenodo (https://zenodo.org/records/10452792), and all data sets and analysis results generated in this work were deposited in Zenodo (https://zenodo.org/records/10052268).

Proguanil synergistically sensitizes ovarian cancer cells to olaparib by increasing DNA damage and inducing apoptosis.

Ovarian cancer is the second leading cause of cancer-related deaths in women, with low five-year survival rates. Therefore, it is essential to seek new treatment options. Olaparib, a PARP inhibitor, has benefited many ovarian cancer patients, but olaparib is much less effective as a single agent in 50% of patients with high grade severe tumors. Proguanil, which was originally developed as an anti-malarial drug, has gained attention due to its anti-tumor effects. Here, we evaluated the anti-tumor effect of the combination of olaparib and proguanil on ovarian cancer cells, aimed to develop a potential medical option for treating ovarian cancer patients. We examined the effect on proliferation by MTT and colony formation assays, while cell migration was measured by the transwell assay. The effect on apoptosis was measured by flow cytometry and AO/EB staining assays. Western blotting was used to detect protein expression levels in cells treated with olaparib and/or proguanil. In addition, the synergistic effect of these two drugs is calculated by CompuSyn software. The combination of olaparib and proguanil significantly increased growth suppression and apoptosis in ovarian cancer cells, compared to either single agent alone. Furthermore, results showed that the combination of olaparib and proguanil synergistically increased olaparib-induced apoptosis and DNA damage and reduced the efficiency of DNA homologous recombination repair. Our findings indicate that combination of olaparib with proguanil will be a novel potential administration route for treating ovarian cancer patients.

Structure-Based Molecular Networking for the Discovery of Anti-HBV Compounds from Saussurea lappa (Decne.) C.B Clarke.

It is a crucial to find target compounds in natural product research. This study presents a concept of structure-guided isolation to find candidate active molecules from herbs. We establish a process of anti-viral sesquiterpene networking. An analysis of the networking suggested that new anti-HBV sesquiterpene may be attributable to eudesmane-, guaiane-, cadinane-, germacane- and bisabolane-type sesquiterpenes. In order to evaluate the efficiency of the structure-based molecular networking, ethanol extract of Saussurea lappa (Decne.) C.B Clarke was investigated, which led to the isolation of two guaiane-type (1 and 14), ten eudesmane-type (2-5 and 8-13), two chain (6 and 7) and one germacrane-type (15) sesquiterpenes, including seven new ones, lappaterpenes A-G (1-7), which are reported on herein. The absolute configurations of the new compounds were established by coupling constants, calculated ECD and ROESY correlations, as well as comparisons of optical rotation values with those of known compounds. The absolute configuration of compound 2 was further confirmed by X-ray diffraction. Compounds 1-15 were evaluated for their potency against hepatitis B virus. Compounds 4, 6, 7 and 9 showed effect on HBsAg with inhibition ratios of more than 40% at 30 µM concentrations. Compounds 14 and 15 inhibited HBsAg secretion with the values of IC50 0.73 ± 0.18 and 1.43 ± 0.54 µM, respectively. Structure-based molecular networking inspired the discovery of target compounds.

Comprehensive Analysis of Tryptic Peptides Arising from Disulfide Linkages in NISTmAb and Their Use for Developing a Mass Spectral Library.

This work presents methods for identifying and then creating a mass spectral library for disulfide-linked peptides originating from the NISTmAb, a reference material of the humanized IgG1k monoclonal antibody (RM 8671). Analyses involved both partially reduced and non-reduced samples under neutral and weakly basic conditions followed by nanoflow liquid chromatography tandem mass spectrometry (LC-MS/MS). Spectra of peptides containing disulfide bonds are identified by both MS1 ion and MS2 fragment ion data in order to completely map all the disulfide linkages in the NISTmAb. This led to the detection of 383 distinct disulfide-linked peptide ions, arising from fully tryptic cleavage, missed cleavage, irregular cleavage, complex Met/Trp oxidation mixtures, and metal adducts. Fragmentation features of disulfide bonds under low-energy collision dissociation were examined. These include (1) peptide bond cleavage leaving disulfide bonds intact; (2) disulfide bond cleavage, often leading to extensive fragmentation; and (3) double cleavage products resulting from breakages of two peptide bonds or both peptide and disulfide bonds. Automated annotation of various complex MS/MS fragments enabled the identification of disulfide-linked peptides with high confidence. Peptides containing each of the nine native disulfide bonds were identified along with 86 additional disulfide linkages arising from disulfide bond shuffling. The presence of shuffled disulfides was nearly completely abrogated by refining digest conditions. A curated spectral library of 702 disulfide-linked peptide spectra was created from this analysis and is publicly available for free download. Since all IgG1 antibodies have the same constant regions, the resulting library can be used as a tool for facile identification of "hard-to-find" disulfide-bonded peptides. Moreover, we show that one may identify such peptides originating from IgG1 proteins in human serum, thereby serving as a means of monitoring the completeness of protein reduction in proteomics studies. Data are available via ProteomeXchange with identifier PXD023358.

Mass Spectral Library of Acylcarnitines Derived from Human Urine.

We describe the creation of a mass spectral library of acylcarnitines and conjugated acylcarnitines from the LC-MS/MS analysis of six NIST urine reference materials. To recognize acylcarnitines, we conducted in-depth analyses of fragmentation patterns of acylcarnitines and developed a set of rules, derived from spectra in the NIST17 Tandem MS Library and those identified in urine, using the newly developed hybrid search method. Acylcarnitine tandem spectra were annotated with fragments from carnitine and acyl moieties as well as neutral loss peaks from precursors. Consensus spectra were derived from spectra having similar retention time, fragmentation pattern, and the same precursor m/z and collision energy. The library contains 157 different precursor masses, 586 unique acylcarnitines, and 4 332 acylcarnitine consensus spectra. Furthermore, from spectra that partially satisfied the fragmentation rules of acylcarnitines, we identified 125 conjugated acylcarnitines represented by 987 consensus spectra, which appear to originate from Phase II biotransformation reactions. To our knowledge, this is the first report of conjugated acylcarnitines. The mass spectra provided by this work may be useful for clinical screening of acylcarnitines as well as for studying relationships among fragmentation patterns, collision energies, structures, and retention times of acylcarnitines. Further, these methods are extensible to other classes of metabolites.

Hybrid Search: A Method for Identifying Metabolites Absent from Tandem Mass Spectrometry Libraries.

Metabolomics has a critical need for better tools for mass spectral identification. Common metabolites may be identified by searching libraries of tandem mass spectra, which offers important advantages over other approaches to identification. But tandem libraries are not nearly complete enough to represent the full molecular diversity present in complex biological samples. We present a novel hybrid search method that can help identify metabolites not in the library by similarity to compounds that are. We call it "hybrid" searching because it combines conventional, direct peak matching with the logical equivalent of neutral-loss matching. A successful hybrid search requires the library to contain "cognates" of the unknown: similar compounds with a structural difference confined to a single region of the molecule, that does not substantially alter its fragmentation behavior. We demonstrate that the hybrid search is highly likely to find similar compounds under such circumstances.

Mass Spectrometry Fingerprints of Small-Molecule Metabolites in Biofluids: Building a Spectral Library of Recurrent Spectra for Urine Analysis.

A large fraction of ions observed in electrospray liquid chromatography-mass spectrometry (LC-ESI-MS) experiments of biological samples remain unidentified. One of the main reasons for this is that spectral libraries of pure compounds fail to account for the complexity of the metabolite profiling of complex materials. Recently, the NIST Mass Spectrometry Data Center has been developing a novel type of searchable mass spectral library that includes all recurrent unidentified spectra found in the sample profile. These libraries, in conjunction with the NIST tandem mass spectral library, allow analysts to explore most of the chemical space accessible to LC-MS analysis. In this work, we demonstrate how these libraries can provide a reliable fingerprint of the material by applying them to a variety of urine samples, including an extremely altered urine from cancer patients undergoing total body irradiation. The same workflow is applicable to any other biological fluid. The selected class of acylcarnitines is examined in detail, and derived libraries and related software are freely available. They are intended to serve as online resources for continuing community review and improvement.

In-Depth Characterization and Spectral Library Building of Glycopeptides in the Tryptic Digest of a Monoclonal Antibody Using 1D and 2D LC-MS/MS.

This work presents a detailed analysis of glycopeptides produced in the tryptic digestion of an IgG1 reference material. Analysis was done by nanospray ESI LC-MS/MS over a wide range of HCD collision energies with both conventional 1D separation for various digestion conditions and a 20 fraction 2D-LC study of a single digest. An extended version of NIST-developed software for analysis of "shotgun" proteomics served to identify the glycopeptides from their precursor masses and product ions for peptides with up to three missed cleavages. A peptide with a single missed cleavage, TKPREEQYNSTYR, was dominant and led to the determination of almost all glycans reported in this study. The 2D studies found a total of 247 glycopeptide ions and 60 glycans of different masses, including 30 glycans found in the 1D studies. This significantly larger number of glycans than found in any other glycoanalysis of therapeutic glycoproteins is due to both the improved separation of sialylated versus asialylated species in the first (high-pH) dimension and the ability to inject large amounts of glycosylated peptides in the 2D studies. Systematic variations in retention with glycan size were also noted. Energy-dependent changes in HCD fragmentation confirmed the proposed glycan structures and led to a peak-annotated mass spectral library to aid the analysis of glycopeptides derived from IgG1 drugs.

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics data sets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and nonreference markers of cancer. The CPTAC laboratories have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these data sets were produced from 2D liquid chromatography-tandem mass spectrometry analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false-discovery rate-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the data sets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level ("rolled-up") precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data to enable comparisons between different samples and cancer types as well as across the major omics fields.

Analysis of human plasma metabolites across different liquid chromatography/mass spectrometry platforms: Cross-platform transferable chemical signatures.

RATIONALE: The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different liquid chromatography/mass spectrometry (LC/MS) platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. METHODS: Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC/MS platforms using reversed-phase chromatography and different chromatographic scales (conventional HPLC, UHPLC and nanoLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). RESULTS: Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (relative standard deviation (RSD) <2%); however, substantial differences were found in the LC/MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. CONLUSIONS: Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable.

Improved normalization of systematic biases affecting ion current measurements in label-free proteomics data.

Normalization is an important step in the analysis of quantitative proteomics data. If this step is ignored, systematic biases can lead to incorrect assumptions about regulation. Most statistical procedures for normalizing proteomics data have been borrowed from genomics where their development has focused on the removal of so-called 'batch effects.' In general, a typical normalization step in proteomics works under the assumption that most peptides/proteins do not change; scaling is then used to give a median log-ratio of 0. The focus of this work was to identify other factors, derived from knowledge of the variables in proteomics, which might be used to improve normalization. Here we have examined the multi-laboratory data sets from Phase I of the NCI's CPTAC program. Surprisingly, the most important bias variables affecting peptide intensities within labs were retention time and charge state. The magnitude of these observations was exaggerated in samples of unequal concentrations or "spike-in" levels, presumably because the average precursor charge for peptides with higher charge state potentials is lower at higher relative sample concentrations. These effects are consistent with reduced protonation during electrospray and demonstrate that the physical properties of the peptides themselves can serve as good reporters of systematic biases. Between labs, retention time, precursor m/z, and peptide length were most commonly the top-ranked bias variables, over the standardly used average intensity (A). A larger set of variables was then used to develop a stepwise normalization procedure. This statistical model was found to perform as well or better on the CPTAC mock biomarker data than other commonly used methods. Furthermore, the method described here does not require a priori knowledge of the systematic biases in a given data set. These improvements can be attributed to the inclusion of variables other than average intensity during normalization.

Tandem mass spectral libraries of peptides in digests of individual proteins: Human Serum Albumin (HSA).

This work presents a method for creating a mass spectral library containing tandem spectra of identifiable peptide ions in the tryptic digestion of a single protein. Human serum albumin (HSA(1)) was selected for this purpose owing to its ubiquity, high level of characterization and availability of digest data. The underlying experimental data consisted of ∼3000 one-dimensional LC-ESI-MS/MS runs with ion-trap fragmentation. In order to generate a wide range of peptides, studies covered a broad set of instrument and digestion conditions using multiple sources of HSA and trypsin. Computer methods were developed to enable the reliable identification and reference spectrum extraction of all peptide ions identifiable by current sequence search methods. This process made use of both MS2 (tandem) spectra and MS1 (electrospray) data. Identified spectra were generated for 2918 different peptide ions, using a variety of manually-validated filters to ensure spectrum quality and identification reliability. The resulting library was composed of 10% conventional tryptic and 29% semitryptic peptide ions, along with 42% tryptic peptide ions with known or unknown modifications, which included both analytical artifacts and post-translational modifications (PTMs) present in the original HSA. The remaining 19% contained unexpected missed-cleavages or were under/over alkylated. The methods described can be extended to create equivalent spectral libraries for any target protein. Such libraries have a number of applications in addition to their known advantages of speed and sensitivity, including the ready re-identification of known PTMs, rejection of artifact spectra and a means of assessing sample and digestion quality.

Metabolite profiling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources.

Recent progress in metabolomics and the development of increasingly sensitive analytical techniques have renewed interest in global profiling, i.e., semiquantitative monitoring of all chemical constituents of biological fluids. In this work, we have performed global profiling of NIST SRM 1950, "Metabolites in Human Plasma", using GC-MS, LC-MS, and NMR. Metabolome coverage, difficulties, and reproducibility of the experiments on each platform are discussed. A total of 353 metabolites have been identified in this material. GC-MS provides 65 unique identifications, and most of the identifications from NMR overlap with the LC-MS identifications, except for some small sugars that are not directly found by LC-MS. Also, repeatability and intermediate precision analyses show that the SRM 1950 profiling is reproducible enough to consider this material as a good choice to distinguish between analytical and biological variability. Clinical laboratory data shows that most results are within the reference ranges for each assay. In-house computational tools have been developed or modified for MS data processing and interactive web display. All data and programs are freely available online at http://peptide.nist.gov/ and http://srmd.nist.gov/ .

Less Is More: Surgical Phase Recognition From Timestamp Supervision.

Surgical phase recognition is a fundamental task in computer-assisted surgery systems. Most existing works are under the supervision of expensive and time-consuming full annotations, which require the surgeons to repeat watching videos to find the precise start and end time for a surgical phase. In this paper, we introduce timestamp supervision for surgical phase recognition to train the models with timestamp annotations, where the surgeons are asked to identify only a single timestamp within the temporal boundary of a phase. This annotation can significantly reduce the manual annotation cost compared to the full annotations. To make full use of such timestamp supervisions, we propose a novel method called uncertainty-aware temporal diffusion (UATD) to generate trustworthy pseudo labels for training. Our proposed UATD is motivated by the property of surgical videos, i.e., the phases are long events consisting of consecutive frames. To be specific, UATD diffuses the single labelled timestamp to its corresponding high confident (i.e., low uncertainty) neighbour frames in an iterative way. Our study uncovers unique insights of surgical phase recognition with timestamp supervision: 1) timestamp annotation can reduce 74% annotation time compared with the full annotation, and surgeons tend to annotate those timestamps near the middle of phases; 2) extensive experiments demonstrate that our method can achieve competitive results compared with full supervision methods, while reducing manual annotation costs; 3) less is more in surgical phase recognition, i.e., less but discriminative pseudo labels outperform full but containing ambiguous frames; 4) the proposed UATD can be used as a plug-and-play method to clean ambiguous labels near boundaries between phases, and improve the performance of the current surgical phase recognition methods. Code and annotations obtained from surgeons are available at https://github.com/xmed-lab/TimeStamp-Surgical.

Does the weekend effect exist for acute type A aortic dissection?-a retrospective case-control study.

Background: The weekend effect refers to the mortality difference for patients admitted/operated on weekends compared to those on weekdays. The study aimed to provide new evidence on the impact of the weekend effect on acute type A aortic dissection (ATAAD). Methods: Primary endpoints were operative mortality, stroke, paraplegia, and continuous renal replacement therapy (CRRT). A meta-analysis of current evidence on the weekend effect was first conducted. Analyses based on single-center data (retrospective, case-control study) were further performed. Results: A total of 18,462 individuals were included in the meta-analysis. The pooled results showed that mortality was not significantly higher for ATAAD on weekends compared to that on weekdays [odds ratio (OR): 1.16, 95% CI: 0.94-1.43]. The single-center cohort included 479 patients, which also showed no significant differences in primary and secondary outcomes between the two groups. The unadjusted OR for weekend group over weekday group was 0.90 (95% CI: 0.40-1.86, P=0.777). The adjusted OR for weekend group was 0.94 (95% CI: 0.41-2.02, P=0.880) controlling for significant preoperative factors, and 0.75 (95% CI: 0.30-1.74, P=0.24) controlling for significant preoperative and operative factors altogether. In PSM matched cohort, the operative mortality was still comparable between the weekend group [10 (7.2%)] and weekday group [9 (6.5%)] (P=1.000). No significant survival difference was observed between the two groups (P=0.970). Conclusions: The weekend effect was not found to be applicable to ATAAD. However, clinicians should be cautious of the weekend effect as it is disease-specific and may vary across healthcare systems.

Surgical repair of unilateral absence of pulmonary artery in children with pulmonary hypertension: a single-center retrospective study.

Background: The early diagnosis of unilateral absence of pulmonary artery (UAPA) in children offers an opportunity for effective intervention. Due to the lack of clinical evidence, a consensus regarding surgical treatment has yet to be reported. The aim of this study is to evaluate the effectiveness and safety of pulmonary artery (PA) reconstruction with a "two-segment" technique to repair UAPA in patients with pulmonary hypertension. Methods: Intraoperatively, the ligamentum arteriosum connecting the innominate artery and distal PA was dissected and occluded. A conduit created by fresh autologous pericardium formed the first "segment" of the neo-PA. The second "segment" was a Gore vascular graft with integrated rings anastomosed between the proximal end of the pericardial conduit and the main pulmonary artery (MPA). Results: A total of five consecutive patients were included, and the absent PA was successfully reconstructed using the "two-segment" technique in all patients. Following revascularization, the direct measurement of the pressure in MPA during the operation showed that the average mean pulmonary artery pressure (mPAP) decreased from 31.3±16.0 to 16.8±4.2 mmHg (P=0.047). The average mPAP/radial mean arterial pressure (rMAP) ratio decreased from 0.59±0.27 preoperatively to 0.30±0.10 postoperatively (P=0.028). The mean follow-up period was 18.85±4.67 months. The median diameter of the reconstructed PA (pericardial segment) measured by transthoracic echocardiography (TTE) was 6.1 mm. One patient safely underwent a redo operation to repair relative stenosis in the neo-PA. Conclusions: Early PA reconstruction may effectively alleviate pulmonary hypertension in children with UAPA. The "two-segment" technique is safe and can facilitate potential redo pulmonary arterioplasty. Anticoagulation and antiplatelet therapy, as well as frequent follow-up, is required after the operation.

Phenformin synergistically sensitizes liver cancer cells to sorafenib by downregulating CRAF/ERK and PI3K/AKT/mTOR pathways.

Sorafenib is a first-line drug to treat advanced hepatocellular carcinoma (HCC), which can prolong the median overall survival of patients by approximately 3 months. Phenformin is a biguanide derivative that has been shown to exhibit antitumor activity superior to that of metformin. We herein explored the ability of phenformin to enhance the anti-cancer activity of sorafenib against HCC and the mechanisms underlying such synergy. The Hep-G2 and SMMC-7721 HCC cell lines were treated with sorafenib and/or phenformin, after which the proliferation of these cells was evaluated via MTT and colony formation assays, while invasion and apoptotic cell death were evaluated via Transwell and flow cytometry assays, respectively. In addition, protein levels were assessed by Western blotting, drug synergy was assessed with the CompuSyn software, and xenograft models were established by implanting Hep-G2 cells into nude mice and then assessing drug antitumor efficacy. Sorafenib and phenformin exhibited a synergistic ability to suppress HCC cell proliferation, migration, and survival. Phenformin further bolstered the ability of sorafenib to inhibit the CRAF/ERK and PI3K/AKT/mTOR pathways. Strikingly, the combination of these two drugs achieved better in vivo efficacy in a murine model system, without causing significant weight loss or hepatorenal toxicity. Sorafenib and phenformin can synergistically suppress CRAF/ERK and PI3K/AKT/mTOR pathway activation in HCC cells, and may thus represent a promising approach to treating this deadly cancer.