To ease the use of these techniques, the Remote Sensing Group has built add-ons for ImageJ. ImageJ is public domain Java image processing software. These add-ons are necessary to process multi-spectral images, and there is now an image read/write module with specific formats for multi-band images (usable for any number of spectral bands).
Additionally, the Remote Sensing Group has developed a module of generic utilities. Another module implements the image transforms most commonly used in image fusion. And yet another includes different multi-spectral and panchromatic image fusion algorithms, including algorithms developed by the Remote Sensing Group, already published in specialized journals.
Some of our planet’s most pressing problems, like population growth, the need for sustainable intensive agriculture, safe food and energy production and distribution, soil management, climate change, public health and social conflicts, cannot be solved without immediate information on a local and a global scale.
Remote sensing is the only available technology at present for acquiring most of this information almost immediately and on any scale, as it supplies a tremendous amount of high quality (accurate, consistent and reliable) geographic, spatial and spectral data, etc.
One of the most commonly used products in remote sensing are images from remote optical sensors: multi-spectral and panchromatic images. A multi-spectral image is an image recorded by a sensor that picks up information contained in different bands of the electromagnetic scale. A multi-spectral image is composed of as many images of the same area of the earth’s surface as spectral bands recorded by the sensor (spectral resolution). Each of these images actually provides information about the amount of radiation reflected by the different surfaces in the area being observed within each of the spectral bands. Another feature of these images is their spatial resolution. Spatial resolution determines the size of the smallest detail that can be observed in the image.
On the other hand, panchromatic images provide the same type of information for a single, normally the broadest, spectral band.
Information extraction methods
The volume of data to be managed and interpreted can vary significantly depending on the sensor type used and the features of the images they record. Even so, data throughput is always very high and calls for objective and precise information extraction methods.
Traditionally these methods have been based on automatic classification and interpretation techniques. On the whole, these techniques output qualitative information that is not always easily quantifiable. Spectral indices or model inversion are other approaches that have recently proved to be more effective for extracting quantitative information from satellite images.
Whatever approach is taken, the precision of the results provided by the remote sensing techniques depends on a series of factors. Current sensor technology (ETM+, ASTER, MERIS, MOS, SPOT, IKONOS, QUICKBIRD...) and, consequently, the features (spatial, spectral and temporal resolution) of the images they record are two key factors. Due to space platform information transmission technology limitations, there is at present a trade-off between these three types of resolution. Sensors that provide a high spatial resolution tend to have a lower spectral resolution and vice versa. This is why panchromatic images have a higher spatial resolution than multi-spectral images. Note, for example, that multi-spectral images from space programmes like LANDSAT, SPOT or IRS, have a high spectral resolution compared with the respective panchromatic images, but their spatial resolution is lower.
Image fusion techniques
Still, there is a wide range of remote sensing applications that require satellite images combining both features (high spatial and spectral resolution).
Even though some of today’s satellites, like QUICKBIRD and IKONOS, do actually deliver such high resolution images, they are costly and not always to be had by ordinary users. One way of getting high resolution spatial and spectral images at fairly reasonable costs is to use image fusion techniques. What’s more, image fusion techniques can output very high resolution images if applied to data recorded by latest generation sensors. The goal of image fusion techniques is to consistently integrate information from different images, assuring that the final fused image retains the key information from the source images.
There are now many optical image fusion methodologies and algorithms. The most common are based on a number of different transforms. Some, like the methodologies based on the Brovey transform, principal component analysis or the IHS transformation method (intensity, hue, saturation), are conceptually very simple.
As demonstrated in many papers, however, the colour of the fused images output by these methodologies is quite distorted compared with the original multi-spectral images. This means that they cannot be used in a variety of routine tasks in the field of remote sensing, like image classification or change detection.
On the other hand, there are many methods based on multi-resolution analysis techniques. Most of these techniques use the discrete wavelet transform (DWT). Generally, these methods provide only a slight distortion of the colour of the fused images with respect to the multi-spectral image. They outperform the techniques described above, but there is no way of controlling the trade-off between the spatial and spectral quality of the fused images.
Remote Sensing Group TechniquesThe School of Computing’s Remote Sensing Group has proposed a weighted version of DWT-mediated fusion calculated using the à trous algorithm. This algorithm can efficiently separate the background information from the detail of an image, avoiding the decimation process characteristic of other algorithms used to calculate the DWT.
The Remote Sensing Group has also proposed other fusion techniques based on multidirection-multiresolution transforms (MDMR). These methods output better quality fused images than DWT-based techniques and, at the same time, have a built-in facility for controlling the trade-off between the images’ spatial quality and colour distortion.
With the aim of easing the use of the proposed algorithms already published in reputed international journals, the Remote Sensing Group set itself the goal of integrating the methods into a tool.
To do this, it set out to build the tools required to process multi-spectral images into public domain image processing software developed in Java: ImageJ.
As mentioned earlier, the modules that are now up and running are:• Image read/write module with specific formats for multi-band images (any number of spectral bands)
All these ImageJ add-ons have been packaged as IJFusion.
Construction of practical quantum computers radically simplified
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In experiments with magnetic atoms conducted at extremely low temperatures, scientists have demonstrated a unique phase of matter: The atoms form a new type of quantum liquid or quantum droplet state. These so called quantum droplets may preserve their form in absence of external confinement because of quantum effects. The joint team of experimental physicists from Innsbruck and theoretical physicists from Hannover report on their findings in the journal Physical Review X.
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The Max Planck Institute for Physics (MPP) is opening up a new research field. A workshop from November 21 - 22, 2016 will mark the start of activities for an innovative axion experiment. Axions are still only purely hypothetical particles. Their detection could solve two fundamental problems in particle physics: What dark matter consists of and why it has not yet been possible to directly observe a CP violation for the strong interaction.
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We present PepQuery2, which leverages a new tandem mass spectrometry (MS/MS) data indexing approach to enable ultrafast, targeted identification of novel and known peptides in any local or publicly available MS proteomics datasets. The stand-alone version of PepQuery2 allows directly searching more than one billion indexed MS/MS spectra in the PepQueryDB or any public datasets from PRIDE, MassIVE, iProX, or jPOSTrepo, whereas the web version enables users to search datasets in PepQueryDB with a user-friendly interface. We demonstrate the utilities of PepQuery2 in a wide range of applications including detecting proteomic evidence for genomically predicted novel peptides, validating novel and known peptides identified using spectrum-centric database searching, prioritizing tumor-specific antigens, identifying missing proteins, and selecting proteotypic peptides for targeted proteomics experiments. By putting public MS proteomics data directly into the hands of scientists, PepQuery2 opens many new ways to transform these data into useful information for the broad research community.
Tandem mass spectrometry (MS/MS)-based shotgun proteomics is the workhorse for protein identification and quantification in biomedical research. Thousands of shotgun proteomics datasets with billions of MS/MS spectra have been generated and deposited into public data repositories such as PRIDE1, MassIVE, iProX2, jPOSTrepo3, and Proteomics Data Commons (PDC). However, it remains challenging to put these public MS proteomics data directly into the hands of scientists to address their research questions, an important step to unleash the full potential of these data.
One way to democratize the use of these public data is to allow users to query peptide or protein sequences of interest against MS/MS spectra in a public data repository to identify high-quality peptide-spectrum matches (PSMs), similar to BLASTing a DNA sequence of interest against a genomic sequence database to identify sequences of high similarity. PSMs identified from the public MS/MS data may provide evidence to support novel peptide predictions4,5,6,7, to prioritize putative tumor-specific antigens8, to uncover “missing” proteins9, among other applications7,10. Many tools, such as MaxQuant11, MS-GF + 12, Comet13, Open-pFind14, and MSFragger15, have been developed to search MS/MS data against a prespecified protein database to identify PSMs, but the common goal of these tools is to comprehensively interpret all observed MS/MS spectra in a study. These spectrum-centric tools are not suitable for peptide-centric analysis that aims to identify one or more peptide or protein sequences of interest, because most of the computational time is spent on evaluating peptide-spectrum pairs irrelevant to the query sequences. Moreover, they typically lack rigorous quality control for individual PSMs.
To complement the spectrum-centric approaches, we have previously developed PepQuery, a peptide-centric search engine for MS/MS data analysis16. PepQuery allows users to query a novel sequence of interest against an MS/MS spectra database to identify statistically significant PSMs. By focusing on only the query sequence of interest, PepQuery bypasses all unnecessary computations, leading to vastly reduced space and time complexity. Moreover, due to increased time efficiency, PepQuery further enables the comprehensive examination of peptide modifications to reduce false discoveries. Most studies using the spectrum-centric database searching tools for peptide identification consider only a small number of protein modifications. As a consequence, false discoveries arise when a spectrum matched to one peptide has a better match to another peptide with a modification not considered in data analysis. This problem is well recognized in novel peptide identification17, and it is also common in normal peptide identification15. Comprehensively considering all types of natural and artificial protein modifications, PepQuery has been shown to be highly effective in reducing false discoveries in novel peptide identification16,18. PepQuery was implemented both as a stand-alone tool and a web application. The stand-alone version supports the analysis of local proteomics datasets. The web version enables web-based analysis of public proteomic datasets available in PepQueryDB, but the analysis is limited to one query sequence and one dataset at a time, and there is no support for direct analysis of MS/MS data in the major proteomics data repositories.
Here we introduce PepQuery2, which leverages a new MS/MS indexing approach and cloud storage to enable ultrafast, targeted identification of both novel and known peptides. The stand-alone version of PepQuery2 allows users to search more than one billion MS/MS data indexed in the PepQueryDB from any computers with internet access. It also supports direct analysis of user-provided MS/MS data, any public datasets in PRIDE, MassIVE, iProX, or jPOSTrepo, or Universal Spectrum Identifiers (USIs)19 from ProteomeXchange (Fig. 1). Meanwhile, we have extended the web version to include public proteomics datasets from all flagship CPTAC studies, leading to a total of 48 datasets. We demonstrate the utilities of PepQuery2 in detecting proteomic evidence for genomically predicted novel peptides, validating novel or known peptides identified from spectrum-centric database searching, prioritizing tumor-specific antigens, identifying missing proteins, and selecting proteotypic peptides for targeted proteomics experiments.
An overview of PepQuery2
One of the fundamental improvements in PepQuery2 is the new MS/MS spectrum indexing by leveraging the cloud storage service (Methods, Supplementary Fig. 1). In brief, MS/MS spectra from a dataset with similar precursor mass after mass binning are stored in a single compressed file on the cloud storage so that candidate spectra matched to a query peptide can be retrieved quickly from large-scale datasets. This new indexing method not only enables ultrafast peptide-spectrum matching but also greatly reduces data storage space compared with the previous SQL-based indexing. More than one billion MS/MS spectra have been indexed and are available in the PepQueryDB, which includes data from 48 large-scale human proteomics datasets of more than 1500 tumors covering 14 types of cancers, 375 cell lines, and more than 30 types of normal tissues (Fig. 1, Supplementary Data 1).
Another major improvement in PepQuery2 enables using known peptide or protein sequences, in addition to novel sequences, as a query sequence (Fig. 1). This is particularly useful for hunting for missing proteins, validating unexpected but interesting identifications, such as tumor-associated antigens, selecting proteotypic peptides for targeted proteomics experiments, and validating peptides identified from small-scale MS experiments, such as affinity purification–mass spectrometry (AP-MS) experiments, in which quality control of protein identification remains challenging. Moreover, in addition to peptide validation, PepQuery2 has been expanded to support PSM validation. This new feature allows users to use the peptide-centric analysis as a complementary approach to validate interesting PSMs identified in spectrum-centric analysis and classify them into seven different categories (c1-c7, Fig. 1, Methods). C1 (exact ref match) includes input PSMs for which the peptide has an exact match to a sequence in the reference database. This is only applicable to novel peptide validation, and PSMs in this category are essentially invalid novel identifications. This could happen when the input PSMs are identified using a different database than the selected reference database in PepQuery2 analysis. C2 (no candidate spectrum) includes input PSMs for which the peptide has no candidate spectrum based on the peptide mass and allowed mass error tolerance. C3 (low score) includes input PSMs with a PepQuery2 computed PSM score lower than a prespecified threshold (Methods). These low-quality matches are excluded from further analysis to save time. C4 (equal or better ref match) includes input PSMs for which the spectrum can be matched to a reference peptide with an equal or better PSM score. C5 (insignificant score) includes input PSMs failing the statistical evaluation based on randomly shuffled peptides (Methods). C6 (better mod ref match) includes input PSMs for which the spectrum can be better matched to a reference peptide with a modification that is not considered in the spectrum-centric analysis. Input PSMs passing all these filtering steps are considered as C7, or confident identifications.
Detecting proteomic evidence for genomically predicted novel peptides
To demonstrate the utility of PepQuery2 in identifying proteomic evidence from public data to support genomically predicted novel peptides, we queried the KRAS G12D peptide (LVVVGADGVGK) against 12 CPTAC global proteomics datasets indexed in PepQueryDB, including 210,282,541 MS/MS spectra from one label-free experiment and 11 tandem mass tag (TMT) experiments spanning 10 cancer types (Methods). We identified 28 PSMs from five cancer types in which KRAS G12D somatic mutation is frequently reported (Fig. 2a, Supplementary Data 2), and a representative MS/MS spectrum identifying the mutant peptide in a pancreatic cancer sample is shown in Fig. 2b. Among the 28 PSMs, 22 were from samples with corresponding genomic mutation, two were from samples without genomic sequencing data, three were from samples with a KRAS G13D mutation, and one was from a sample with an HRAS G12D mutation. Of note, the HRAS G12D peptide is the same as the KRAS G12D peptide, and the KRAS G13D peptide (LVVVGAGDVGK) is hard to distinguish from the KRAS G12D peptide (LVVVGADGVGK) based on MS/MS spectrum since there is only a minor difference between the two sequences. These data suggest high specificity of the PepQuery2 analysis despite the huge search space, including >210 million MS/MS spectra. Meanwhile, among the 75 tumor samples with the KRAS G12D mutation detected at DNA level, 41 (55%) had protein evidence from the PepQuery2 analysis (Fig. 2a). The sensitivity of 55% (41/75) is outstanding considering the well-recognized low sensitivity of MS proteomics in detecting mutant peptide20. Importantly, the whole analysis took less than four minutes on a Linux server with 40 threads, or five minutes on a Mac computer using eight threads. With the spectrum-centric approach, the same task would take several days for data downloading, customized database preparation, and database searching.
Validating novel peptide identifications
Another utility of PepQuery2 is to validate novel peptides identified in customized database-based spectrum-centric analysis, in which false discovery is a major concern17,18. We illustrated this feature by validating novel peptides resulted from tryptophan-to-phenylalanine codon reassignment (W > F), which has recently been reported to occur frequently in human cancer21. In the original study21, a total of 473 peptides with W > F substitution were matched to 3011 spectra from the CPTAC lung squamous cell carcinoma (LSCC) dataset22 using a customized database searching strategy. Strikingly, only 9.2% of the PSMs reported in the original study passed PepQuery2 validation (C7 group in Fig. 3a, Supplementary Data 3), corresponding to a 13.5% (64 out of 473) validation rate at the peptide level. The group of PSMs passing PepQuery2 validation (C7) had significantly higher PSM scores (i.e., PeptideProphet probability scores) in the original study compared with the other groups except for C1 and C2 (Fig. 3b). Peptides in the C1 group had exact matches to sequences in the reference database used in the PepQuery2 analysis. These are high-quality identifications as indicated by excellent PeptideProphet probability scores, but they do not qualify as novel peptides because they can be mapped to reference sequences in GENCODE. The C2 group included only 0.2% of the PSMs for which PepQuery2 failed to retrieve candidate spectra based on the pre-specified mass error tolerance. The C3 and C5 groups accounted for 11% of the previously reported PSMs, and they failed PepQuery2 validation due to low and insignificant PSM scores, respectively (Methods). The C4 group, in which the spectra had better matches to a reference peptide when considering both fixed and variable modifications specified in the original search, included 36.9% of the PSMs, and for an additional 36.7% (C6 group), the spectra had better matches to a reference peptide with modifications that were not considered in the original database searching. Within the C4 group, 48% had better matches to a reference peptide containing an amino acid W (Fig. 3c-d, Supplementary Fig. 2), and these potential false identifications from the original study can be attributed to the lack of competition from peptides containing amino acid W because in the customized database used in the original study, all Ws were replaced with an F without keeping a version of the unaltered sequence. Using Delta RT, the absolute difference between observed retention time (RT) and deep learning-predicted RT of the same peptide, as an additional evaluation metric18, we further showed that the PSMs passing PepQuery2 validation had significantly lower delta RT compared with those failing validation (Fig. 3e). Repeating the spectrum-centric analysis using a customized database including human reference proteins downloaded from UniProt (Methods) reduced the total number of candidate peptides with W > F substitution from 473 to 240 (1024 PSMs) and the proportion of the C4 group in PepQuery2 validation to 27% (Supplementary Fig. 2b). Despite these improvements, there were still many candidate PSMs failing PepQuery2 validation, including 510 PSMs (50%) for which the spectrum was matched to a reference peptide with a modification not considered in the spectrum-centric analysis (C6). Together, these results demonstrate PepQuery2 as an effective tool for identifying mistakes in customized database construction (a task not required for PepQuery2 analysis) as well as potential false positives among the novel peptides identified in spectrum-centric analysis.
Validating known peptide identifications
False discoveries are not unique to novel peptide identifications. For example, validation of known peptide identifications using alternative computational algorithms is very useful for small-scale MS experiments, such as AP-MS. Due to limited number of proteins present in an MS sample in these experiments, the normally used target-decoy-based strategy23 may not be able to provide accurate false discovery rate (FDR) estimation. The peptide-centric analysis in PepQuery2 does not rely on the traditional target-decoy strategy used for global FDR estimation and thus provides a statistically unrelated method for validating spectrum-centric analysis results. With the new improvement that allows using known peptide or protein sequences as a query sequence, such validation is now possible in PepQuery2. To illustrate this utility, we applied PepQuery2 to validate prey proteins identified when HDAC1 was used as the bait in AP-MS experiments performed on the 293 T cell line in the BioPlex 3.0 project24. Using PepQuery2 to query the 86 prey proteins identified in the original study against MS/MS data available in MassIVE, 85 passed the validation but one failed. CHD5 is the prey protein failing PepQuery2 validation, and the original identification was based on one unique CHD5 peptide. All spectra associated with the originally reported PSMs identifying this peptide had equal or better match to a peptide from CHD4 with deamination (Fig. 4a, Supplementary Fig. 3), a modification not considered in the original analysis. CHD4, but not CHD5, is a known component in HDAC1-containing protein complexes in the CORUM database, such as the nucleosome remodeling and deacetylation complex (Fig. 4b), and 80 spectra from the same AP-MS experiments were matched to 25 unique peptides from CHD4. These data suggest that CHD5 is likely to be a false identification in the original analysis. In addition to the HDAC1 experiment, AP-MS experiments performed on the 293 T cell line in the BioPlex 3.0 project for 11 other bait proteins identified CHD5 as a prey protein. Ten out of these 11 identifications failed PepQuery2 validation for the same reason.
Even in large-scale MS experiments where peptide identification FDR can be well controlled, further validation is still useful, especially for unexpected identifications with important biological or clinical implications. As an example, PGK2 was identified and quantified in the CPTAC lung adenocarcinoma (LUAD) global proteome dataset both in the original publication25 using the Spectrum Mill search engine and in an independent analysis using FragPipe. PGK2 was initially assumed to be a pseudogene but was later found to have highly specific expression in testis26. The detection of PGK2 in the LUAD cohort was unexpected. Moreover, a peptide (AVVLMSHLGRPDGVPMPDK) supporting the detection of PGK2 was identified in all samples with high abundance (Fig. 4c), and the abundance in tumors was significantly higher than in adjacent normal tissues (p < 2.2e-16, two-sided Wilcoxon Rank Sum test, Fig. 4c-d), suggesting PGK2 as a possible cancer/testis (CT) antigen and a putative immunotherapy target for lung cancer treatment. To further investigate this intriguing finding with potential clinical significance, we used PepQuery2 to validate all 239 PSMs reported by FragPipe for PGK2. Remarkably, 94% (224) of the PSMs, including all 102 PSMs identifying the highly abundant peptide, failed the validation (Fig. 4c). The spectra matched to the peptide AVVLMSHLGRPDGVPMPDK by FragPipe were found by PepQuery2 to have a better match to another peptide SVVLMSHLGRPDGVPMPDK from the homologous protein PGK1 (Supplementary Fig. 4). Further investigation showed that the PGK2 protein abundance quantified by FragPipe is highly correlated with the PGK1 protein abundance (Fig. 4d), whereas the PGK2 mRNA abundance does not correlate with PGK1 mRNA abundance in the same tumor cohort, and all tumors had very low PGK2 mRNA abundance, including more than half with no PGK2 mRNA detection (Fig. 4e). PGK2 identification was also reported in a colon cancer study27, where the supporting PSMs also failed PepQuery2 validation because the associated spectra had an equal or better match to PGK1 peptides (Methods, Supplementary Fig. 5). PGK2 is not an exception. As another example, NAA11, a protein shown restricted expression in reproductive tissues in Human Protein Atlas, was also identified by FragPipe in the CPTAC LUAD dataset. All PSMs from this protein failed PepQuery2 validation because the associated spectra had equal or better match to a homologous peptide from NAA10, and correlation analyses between NAA10 and NAA11 at protein and mRNA levels provided further evidence to confirm the invalidity of the NAA11 identification and quantification (Supplementary Fig. 6). These results demonstrate the power of PepQuery2 as a validation tool to safeguard the quality of unexpected normal peptide identifications to prevent unnecessary downstream experimental and clinical investigations.
Prioritizing tumor-specific antigens
In addition to validating peptide identifications using publicly available data from the same study, PepQuery2 can also be used to search interesting peptides identified from one study in other public datasets to gain new insights. A recent cancer immunopeptidomics study identified major histocompatibility complex (MHC) bound peptides from 576 novel or unannotated open reading frames (nuORFs) in cancer immunopeptidomics data28. These nuORFs greatly expand the cancer antigen repertoire and putative immunotherapy targets. To test their cancer specificity, we queried these nuORFs against a published heathy tissue dataset containing proteomics data (68,225,841 MS/MS spectra) from 31 heathy tissues29. Among the 576 nuORFs, 201 (35%) were detected in at least one and 83 (14%) in two or more healthy tissues (Fig. 5, Supplementary Data 4). Thus, PepQuery2 quickly narrowed down the list of nuORFs for further investigation as candidate neoantigens.
Hunting for missing proteins
In the human proteome project (HPP), human proteins in the neXtProt database are classified into different categories based on the strength of supporting evidence9. A total of 1343 proteins are still classified as “missing proteins” due to the lack of experimental evidence at the protein level, and an important goal of the HPP is to hunt for the missing proteins in human proteome9. To look for MS-based experimental evidence for the 1343 missing proteins from public proteomics data, we used PepQuery2 to query these proteins against all datasets in PepQueryDB, including >1 billion MS/MS spectra. Following the HPP guideline for missing protein identification30, 48 missing proteins were identified with two or more unique peptides detected in at least one dataset, and all of them had peptide evidence in multiple datasets (Fig. 6, Supplementary Data 5, Methods). These proteins could serve as candidates for further validation using targeted proteomics with synthetic peptides or functional studies. This quick analysis brought the missing protein search a step closer to completion.
Guiding the selection of proteotypic peptides for targeted proteomics
In targeted proteomics experiments, one of the critical steps is proteotypic peptide selection for the proteins of interest31. Analyzing public proteomics datasets could provide valuable empirical data to guide the selection of proteotypic peptides. Because public PTM proteomics data can also be included in the search, such analysis may also identify PTM peptides for targeted proteomics. As an example, we applied PepQuery2 to identify peptides specific to two protein isoforms of the gene XBP1 (X-box binding protein 1), the conventionally spliced isoform XBP1u and the non-conventionally spliced isoform XBP1s. Importantly, unconventional splicing of XBP1 mRNA by IRE1α is an indicator of unfolded protein response and plays an important role in several diseases, including cancer32,33. We searched the two protein isoforms against all the datasets available in PepQueryDB and detected four peptides from XBP1u, five peptides from XBP1s, and 19 peptides shared by the two isoforms (Fig. 7). Interestingly, all four peptides from XBP1u were detected from global proteome datasets, whereas four out of the five peptides from XBP1s were detected from phosphoproteome datasets. Thus, our analysis not only identified isoform-specific peptides but also showed that including phosphorylated peptides as targets may increase the chance of detecting XBP1s. In addition to guiding peptide selection, the identified spectra by directly searching MS/MS data also provide valuable information for transition list generation in multiple reaction monitoring (MRM)-based targeted assays. Since PepQuery2 not only enables searching more than one billion MS/MS spectra from a diverse collection of cancers, cell lines, and normal tissues in PepQueryDB but also allows searching other MS/MS data in public proteomics data repositories such as PRIDE, the large volume of MS/MS data in these repositories could be readily used to guide targeted experiment design for proteins of interest.
One of the most important milestones in proteomics is the Amsterdam Principles34, which require mandatory raw MS/MS data deposition to promote broad reuse of the data. However, because of the challenges involved in understanding, downloading, analyzing, and interpreting MS/MS data, investigation and reuse of these public data are largely restricted to computational proteomics researchers. By enabling rapid identification of any known or novel peptide sequences of interest in any local or publicly available MS-based proteomics datasets in a targeted manner, PepQuery2 provides a practical solution that makes public MS/MS data easily useful to the general research community.
Recently, there is an increasing trend of reusing public proteomics data, especially in the context of searching for proteomic evidence of novel peptides and proteins with important biological and clinical implications. Unfortunately, usage complexity and often-overlooked inherent limitations of the spectrum-centric database searching tools may lead to false discoveries in such studies, as exemplified in the recently reported identification of W > F substitutants from previously published CPTAC MS/MS data21 (Fig. 3). We further showed that false discoveries are also common in the identification of known proteins (Fig. 4). Our peptide-centric analysis complements the spectrum-centric database searching algorithms and provides an efficient framework for validation of important findings.
Both PepQuery and PepQuery2 use stringent criteria for novel peptide validation. When a candidate novel peptide and a reference peptide have equal matching score to a spectrum, the spectrum is preferentially associated with the reference peptide based on the consideration that the prior probability of observing a novel peptide is much lower than a reference peptide. The competitive filtering step based on unrestricted modification searching further excludes the possibility that the spectrum has a better match to a reference peptide sequence with a modification not considered in the spectrum-centric analysis. When two peptides have equal or close scores to the same spectrum, it is very useful to manually check the matches. The web server of PepQuery2 provides annotated spectra for visual check of the matches. For the standalone version, details required for manual checking can be exported for visualization using PDV35. In this study, we also identified independent evidence to support PepQuery2 results. For the W2F peptide validation, we used a metric derived from retention time prediction to evaluate the quality of the results. For the cases of PGK2 and NAA11, we made use of paired mRNA data to support PepQuery2 results. For CHD5, we used prior knowledge about protein complex. Such analyses are very helpful in evaluating matches with equal or similar scores.
The new MS/MS data indexing method implemented in PepQuery2 enables retrieving candidate spectra from a large-scale proteomics dataset for a single peptide in seconds (Supplementary Fig. 1). In conjunction with cloud-based data storage technology, this new method makes it possible to conveniently query more than one billion indexed MS/MS spectra in PepQueryDB from any computer with internet connection. This radically increased the scalability and usability compared with the previous version of PepQuery. The indexing technology should have wide applications in other computational tools for MS proteomics data analysis. Moreover, it can be equally applied to other MS-based omics technologies, such as metabolomics, to enable fast, targeted data analysis.
We have demonstrated the utility of PepQuery2 in a wide range of applications, but its potential is not limited to these applications. By putting public MS proteomics data directly into the hands of scientists, PepQuery2 will open many new ways to transform these data into useful information for the broad research community.
MS/MS data indexing and the construction of PepQueryDB
Instead of the SQL-based MS/MS indexing method, which was used in the previous version of PepQuery, a completely redesigned indexing scheme was used in PepQuery2. Specifically, for each MS/MS dataset, MS/MS spectra with similar precursor mass after mass rounding and binning are stored in a single compressed MGF file on cloud storage or local storage so that the spectra matched to a query peptide can be retrieved quickly even for large datasets (Supplementary Fig. 1). By default, precursor mass binning of 0.1 Da was used. For example, after mass rounding and binning, MS/MS spectra with precursor mass 1000.11 Da and 1000.12 Da are stored in the file named “10001.mgf.gz” file. The file name after removing the file suffix (.mgf.gz) is the processed mass after mass rounding, and all MS/MS spectra in the same file have the same processed mass. If precursor charge is not available for a spectrum, charge 2+ and 3+ will be considered by default in the indexing process. With this indexing scheme, for a query peptide sequence, the peptide masses after considering possible fixed and variable modifications were rounded using the same way, then the candidate spectra could be retrieved quickly using the processed peptide mass (Supplementary Fig. 1).
We reconstructed the PepQueryDB using this new indexing method and expanded the database to include more than one billion MS/MS spectra from more than 40 datasets. The expanded database includes all public large CPTAC proteomics datasets. All indexed MS/MS datasets are stored in a public cloud repository. The indexed datasets can be accessed through both the PepQuery2 command line version and the web server version. For each indexed dataset, the parameters used for MS/MS matching are predefined in PepQuery2 based on the experimental protocol for data generation. This removes the requirement to set MS/MS searching parameters by users and thus makes the data usable to a more general audience, including scientists who are not familiar with proteomics experiments and informatics.
Searching MS/MS data in public proteomics data repositories
Any MS/MS datasets publicly available at PRIDE, MassIVE, jPOSTrepo, or iProX, or USIs from ProteomeXchange, can be directly used by the command line version of PepQuery2. Specifically, for a given dataset with a dataset identifier from these databases, the data files recognized by a specified pattern (such as “.mgf” or “cell_line.*.mgf”) are automatically downloaded and indexed. Then the indexed MS/MS data are used for peptide identification in PepQuery2. MS/MS data files in the format of mgf, mzML, mzXML, and raw MS/MS are supported. If the MS/MS data files are raw MS/MS data, ThermoRawFileParser36 is used to convert the raw MS/MS data to either mgf or mzML format data for MS/MS indexing.
Support for the search of known peptides or proteins
The previous version of PepQuery only supports the analysis of novel peptides, and PepQuery2 allows using known peptide or protein sequences as a query sequence. In the mode of searching for a known peptide, the peptide is allowed to be present in the reference protein database used by PepQuery2. After digestion of the reference protein database, the query peptides are removed and all other peptides are used for competitive filtering based on reference sequences and competitive filtering based on unrestricted post-translational modification searching16. All other processing steps are the same as the novel peptide search workflow.
In the mode of searching for a known protein, the query protein is removed from the reference database. The new reference database without the query protein is then used by PepQuery2. Thus, the query protein is treated as a novel protein and the same workflow for novel protein analysis is used for the search. Only peptides that are unique to the query protein are considered in the search.
Support for PSM validation
A new mode was implemented in PepQuery2 to support PSM validation. In this mode, both query peptide sequence and the associated spectrum identifiers are required as input. For each query peptide, only the spectra with the specified identifiers are retrieved and scored in PepQuery2. The input PSMs are classified into seven categories on the basis of PepQuery2 identification results, including C1) exact ref match, which means that the query peptide has an exact match to a sequence in the reference database used by PepQuery2. This is only applicable to novel peptide validation; C2) no candidate spectrum, which means there is no spectrum that can be matched to the query peptide based on the peptide mass and allowed mass error tolerance; C3) low score, which indicates that the PSM score computed by PepQuery2 is lower than the prespecified threshold (12 is the default); C4) better ref match, which means that the spectrum can be matched to a peptide in the reference database with an equal or better score. This category is generated based on the result from the competitive filtering based on reference sequences (step 3 in Fig. 1); C5) insignificant score, which means that the PSM fails to pass the statistical evaluation (step 4 in Fig. 1) based on shuffled peptides; C6) better mod ref match, which means that the spectrum can be matched to a reference peptide with a modification that is not typically considered in spectrum-centric database searching. This category is generated based on the result from the competitive filtering through unrestricted modification searching (step 5 in Fig. 1), as described previously16. Briefly, all modifications from Unimod are considered in the search. If a spectrum has a better match to a modified peptide from the reference protein database than to the target peptide, the original identification is classified as C6; and C7) confident, which includes PSM passing all the filtering steps as shown in Fig. 1.
PepQuery2 uses the same peptide spectrum match (PSM) scoring and statistical evaluation algorithms as described in the original PepQuery publication16. In brief, two PSM scoring algorithms, Hyperscore37 and MVH38, were implemented. For statistical evaluation of each PSM, randomly shuffled sequences derived from the peptide in the PSM are used to evaluate the statistical significance of the match. The default threshold for p-value filtering is 0.01 for peptides longer than 8 and 0.05 for peptides with length equal or shorter than 8.
Identifying novel peptides resulted from the KRAS G12D mutation
The KRAS G12D mutation peptide LVVVGADGVGK was searched against the global proteome datasets from 10 CPTAC cancer cohorts (CPTAC-BRCA, CPTAC-CCRCC, CPTAC-COAD, CPTAC-GBM, CPTAC-HNSCC, CPTAC-LSCC, CPTAC-LUAD, CPTAC-OV, CPTAC-PDAC and CPTAC-UCEC). A total of 210,282,541 MS/MS spectra were included in the datasets. The protein database from the GENCODE Human release 34 was used as the reference database. The predefined parameters for each dataset in PepQuery2 were used in the analysis. The KRAS mutations detected at the DNA level for tumor samples analyzed in these datasets were downloaded from LinkedOmics [http://linkedomics.org]. Because one TMT sample included multiple tumor samples, a PSM was considered to be supported by genomics data if the KRAS G12D mutation was detected at the DNA level in any of the tumor samples included in the TMT experiment from which the PSM was identified.
Validating novel peptides with W to F substitution
A total of 473 novel peptides with amino acid W to F substitution were collected from a recent publication21. These novel peptides were identified in the CPTAC LSCC global proteome dataset22, in which 3011 PSMs supporting these novel peptides were reported21. The PSM level data was obtained through personal communication with the authors of the original study. These PSMs were validated using PepQuery2. Based on the original study21, the following parameters were used in PepQuery2 validation: Fixed modifications, Carbamidomethyl (C) and TMT 10-plex (K); Variable modifications, Oxidation (M), TMT 10-plex (N-term), TMT 10-plex (S) and Acetylation of peptide N-term; Precursor ion mass tolerance, 20 ppm; MS/MS mass tolerance, 0.05 Da; Enzyme specificity, trypsin; maximum missed cleavages, 2; The range of allowed isotope peak errors, −1,0,1,2,3. The protein database from GENCODE Human release 34 was used as the reference database.
To further assess the quality of peptide identification, the metric derived from peptide retention time prediction based on AutoRT18 was used. As described in our previous publication25, an RT prediction model was trained for each run of MS experiment based on the identified peptides from known reference proteins. The training data was generated based on the PSM level identification result from the CPTAC LSCC global proteome dataset in the original study21. Only the variable modifications Oxidation (M) and TMT 10-plex (S) were considered. The modifications Carbamidomethyl (C), TMT 10-plex (K) and TMT 10-plex (N-term) were considered as fixed modification in AutoRT model training. Any peptides without the modification TMT 10-plex (N-term) were discarded in RT model training and prediction. For a peptide form with multiple spectra identified, the average RT of these spectra was used as the RT for the peptide form. In model training and testing, any peptides for which the difference between the maximum observed RT and minimum observed RT was > 3 min were removed. In model training, the base size was set to 64 and a maximum of 40 epochs was used. Early stop was also used in model training. After RT models were trained, for each PSM from a novel peptide, the RT of the novel peptide was predicted based on the RT model trained using the data from the run of MS experiment in which the spectrum was identified. Then the absolute difference between the predicted RT and observed RT, i.e., delta RT, was calculated and used as a metric to assess the quality of peptide identification.
A reanalysis was performed by searching the CPTAC LSCC global proteome dataset against a new customized database which contained the customized database used in the original study as well as human reference proteins downloaded from UniProt (downloaded on 12/19/2022, 103,830 proteins). The searching was done through FragPipe (v18.0) powered by the MSFragger15 (v3.4) search engine and the Philosopher toolkit39 (v4.4). The parameters were set based on descriptions in the original study21. PepQuery validation was performed with the same parameters as described above.
Known protein validation in small size of MS/MS data
The data for bait protein HDAC1 in AP-MS experiments performed on the 293 T cell line in the BioPlex 3.024 project was accessed from MassIVE through the accession number MSV000088555. A total of 86 prey proteins identified from the experiments were downloaded from https://bioplex.hms.harvard.edu. To validate these prey proteins using PepQuery2, for each protein, all protein isoforms from the UniProt human reference proteome database (04/26/2022) were validated together using PepQuery2. After in silico enzyme digestion, only the peptides uniquely mapped to these protein isoforms were included in the validation, and any peptides that could be mapped to any other proteins were discarded. A peptide shared by different isoforms from the same pray protein but not shared by any other proteins were included in the validation. The following parameters were used in PepQuery2 validation: Variable modifications, Oxidation of M; Precursor ion mass tolerance, 50 ppm; MS/MS mass tolerance, 0.05 Da; Enzyme specificity, trypsin; maximum missed cleavages, 2; The range of allowed isotope peak errors, 0,1. The UniProt human reference proteome database (04/26/2022) was used as the reference database.
Known protein validation in large size of MS/MS data
Protein identification and quantification results for PGK1, PGK2, NAA10, and NAA11 in the CPTAC LUAD global proteome dataset based on both the original publication25 and a reanalysis using the FragPipe pipeline [https://fragpipe.nesvilab.org/] were downloaded from LinkedOmics. mRNA quantification for these genes in the same samples were also downloaded from LinkedOmics. The PSMs identifying PGK2 and NAA11 were retrieved and validated by PepQuery2 using the following parameters: Fixed modifications, Carbamidomethyl (C) and TMT 10-plex (K); variable modifications, Oxidation (M), TMT 10-plex (N-term), TMT 10-plex (S); Precursor ion mass tolerance, 20 ppm; MS/MS mass tolerance, 0.05 Da; Enzyme specificity, trypsin; maximum missed cleavages, 1; The range of allowed isotope peak errors, −1,0,1,2,3. The protein database from GENCODE Human release 34 was used as the reference database.
The MS/MS data from the proteome of metastatic cells in colorectal cancer27 was accessed from MassIVE through the accession number MSV000088431. The reanalysis result of this dataset was downloaded from MassIVE through the accession number RMSV000000617. The PSMs identified from PGK2 were retrieved from this reanalysis and validated using PepQuery2 using the following parameters: fixed modifications, Carbamidomethyl (C); variable modifications, Lysine 13 C(6), Arginine 13 C(6), Oxidation of M, Deamidation of N; Precursor ion mass tolerance, 50 ppm; MS/MS mass tolerance, 0.6 Da; Enzyme specificity, trypsin; maximum missed cleavages, 2. The protein database from GENCODE Human release 34 was used as the reference database.
Identification of nuORFs in healthy tissue data
A total of 576 nuORFs identified in cancer immunopeptidomics data were collected from a previous study28. The protein sequences of these nuORFs were downloaded from MassIVE through the accession number MSV000084787. The raw MS/MS data from a previously published proteomic study analyzing 31 healthy human tissues29 were downloaded from PRIDE through the accession number PXD010154. Downloaded MS/MS data were indexed and included in the PepQueryDB. The nuORFs were searched against this MS/MS dataset. The predefined parameter set was used. The reference protein database from the previous study was used as the reference database.
Missing protein identification
The missing proteins were downloaded from neXtProt [https://www.nextprot.org/, 04/14/2022]. The missing proteins classified as PE2 (evidence only at transcript level), PE3 (inferred from homology) or PE4 (proteins inferred to exist) were searched against all MS/MS datasets in PepQueryDB. The predefined parameter set for each dataset was used. In PepQuery2 analysis, all amino acid substitutions from the UniMod database were considered. This was used to filter out any spectra matched to a missing protein but could also be matched equally or better to any other non-missing proteins with an amino acid substitution. Any unique peptides passing the validation of both scoring algorithms (Hyperscore and MVH) implemented in PepQuery2 were included in downstream analyses. A missing protein was considered to be confidently identified if: (1) at least two unique non-nested peptides with length equal or greater than 9 amino acids were identified in the same dataset; and (2) the missing protein was identified in at least two datasets with at least one unique peptide with length equal or greater than 7 amino acids.
Protein isoform identification
The two protein isoforms of gene XBP1 (XBP1u and XBP1s) were downloaded from UniProt. The isoform XBP1u (P17861-1) is also known as unprocessed XBP1, whereas the isoform XBP1s (P17861-2) is also known as processed XBP1. The two isoforms were searched against all MS/MS datasets in PepQueryDB. The predefined parameter set for each dataset was used. The SwissProt human protein database, including protein isoforms (05/17/2022) was used as the reference database.
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
The 48 MS/MS datasets indexed in PepQueryDB were downloaded from PDC, PRIDE, or MassIVE. Detailed dataset information, including hyperlinks to access the datasets, is available in Supplementary Data 1. The KRAS mutations detected at the DNA level for CPTAC tumor samples were downloaded from LinkedOmics. The human reference proteins used in the reanalysis of the CPTAC LSCC global proteome dataset were downloaded from UniProt on 12/19/2022. The AP-MS data from BioPlex 3.024 was downloaded from MassIVE through the accession number MSV000088555. The human reference proteins used in the analysis of the AP-MS data were downloaded from UniProt on 04/26/2022. The MS/MS data from the proteome of metastatic cells in colorectal cancer27 was accessed from MassIVE through the accession number MSV000088431, and the protein database from GENCODE Human release 34 was used as the reference database for this analysis. The protein sequences of the nuORFs were downloaded from MassIVE through the accession number MSV000084787. The raw MS/MS data from the analyzing 31 healthy human tissues were downloaded from PRIDE through the accession number PXD010154. The missing proteins were downloaded from neXtProt (04/14/2022). For the XBP1 analysis, the SwissProt human protein database, including protein isoforms (05/17/2022) was used as the reference database. Source data are provided with this paper.
Both the command line version and the web version of PepQuery2 are available at [http://www.pepquery.org]. The source code of PepQuery2 is available at [https://github.com/bzhanglab/PepQuery]. Scripts used in the manuscript are available at https://github.com/wenbostar/pepquery2_manuscript.
Perez-Riverol, Y. et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Res. 50, D543–D552 (2022).
Chen, T. et al. iProX in 2021: connecting proteomics data sharing with big data. Nucleic Acids Res. 50, D1522–D1527 (2022).
Okuda, S. et al. jPOSTrepo: an international standard data repository for proteomes. Nucleic Acids Res. 45, D1107–D1111 (2017).
Wright, J. C. et al. Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow. Nat. Commun. 7, 11778 (2016).
Castellana, N. E. et al. Discovery and revision of Arabidopsis genes by proteogenomics. Proc. Natl Acad. Sci. USA 105, 21034–21038 (2008).
Hari, P. S. et al. Proteogenomic Analysis of Breast Cancer Transcriptomic and Proteomic Data, Using De Novo Transcript Assembly: Genome-Wide Identification of Novel Peptides and Clinical Implications. Mol. Cell Proteom. 21, 100220 (2022).
Martens, L. & Vizcaino, J. A. A Golden Age for Working with Public Proteomics Data. Trends Biochem Sci. 42, 333–341 (2017).
Kahles, A. et al. Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients. Cancer Cell 34, 211–224 e216 (2018).
Baker, M. S. et al. Accelerating the search for the missing proteins in the human proteome. Nat. Commun. 8, 14271 (2017).
Vaudel, M. et al. Exploring the potential of public proteomics data. Proteomics 16, 214–225 (2016).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Kim, S. & Pevzner, P. A. MS-GF+ makes progress towards a universal database search tool for proteomics. Nat. Commun. 5, 5277 (2014).
Eng, J. K., Jahan, T. A. & Hoopmann, M. R. Comet: an open-source MS/MS sequence database search tool. Proteomics 13, 22–24 (2013).
Chi, H. et al. Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine. Nat. Biotechnol. (2018).
Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D. & Nesvizhskii, A. I. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics. Nat. Methods 14, 513–520 (2017).
Wen, B., Wang, X. & Zhang, B. PepQuery enables fast, accurate, and convenient proteomic validation of novel genomic alterations. Genome Res 29, 485–493 (2019).
Nesvizhskii, A. I. Proteogenomics: concepts, applications and computational strategies. Nat. Methods 11, 1114–1125 (2014).
Wen, B., Li, K., Zhang, Y. & Zhang, B. Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis. Nat. Commun. 11, 1759 (2020).
Deutsch, E. W. et al. Universal Spectrum Identifier for mass spectra. Nat. Methods 18, 768–770 (2021).
Ruggles, K. V. et al. An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer. Mol. Cell Proteom. 15, 1060–1071 (2016).
Pataskar, A. et al. Tryptophan depletion results in tryptophan-to-phenylalanine substitutants. Nature 603, 721–727 (2022).
Satpathy, S. et al. A proteogenomic portrait of lung squamous cell carcinoma. Cell 184, 4348–4371 e4340 (2021).
Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007).
Huttlin, E. L. et al. Dual proteome-scale networks reveal cell-specific remodeling of the human interactome. Cell 184, 3022–3040 e3028 (2021).
Gillette, M. A. et al. Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma. Cell 182, 200–225 e235 (2020).
McCarrey, J. R. & Thomas, K. Human testis-specific PGK gene lacks introns and possesses characteristics of a processed gene. Nature 326, 501–505 (1987).
Mendes, M. et al. Mapping the Spatial Proteome of Metastatic Cells in Colorectal Cancer. Proteomics 17 (2017).
Ouspenskaia, T. et al. Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer. Nat. Biotechnol. 40, 209–217 (2022).
Wang, D. et al. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Mol. Syst. Biol. 15, e8503 (2019).
Deutsch, E. W. et al. Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0. J. Proteome Res 18, 4108–4116 (2019).
van Bentum, M. & Selbach, M. An Introduction to Advanced Targeted Acquisition Methods. Mol. Cell Proteom. 20, 100165 (2021).
Chen, X. et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1alpha pathway. Nature 508, 103–107 (2014).
Song, M. et al. IRE1alpha-XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity. Nature 562, 423–428 (2018).
Rodriguez, H. et al. Recommendations from the 2008 International Summit on Proteomics Data Release and Sharing Policy: the Amsterdam principles. J. Proteome Res 8, 3689–3692 (2009).
Li, K., Vaudel, M., Zhang, B., Ren, Y. & Wen, B. PDV: an integrative proteomics data viewer. Bioinformatics 35, 1249–1251 (2019).
Hulstaert, N. et al. ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. J. Proteome Res 19, 537–542 (2020).
Craig, R. & Beavis, R. C. TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20, 1466–1467 (2004).
Tabb, D. L., Fernando, C. G. & Chambers, M. C. MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis. J. Proteome Res 6, 654–661 (2007).
da Veiga Leprevost, F. et al. Philosopher: a versatile toolkit for shotgun proteomics data analysis. Nat. Methods 17, 869–870 (2020).
This study was supported by the National Cancer Institute (NCI) CPTAC award U24 CA210954 (B.Z.), the Cancer Prevention & Research Institutes of Texas (CPRIT) award RR160027 (B.Z.), and funding from the McNair Medical Institute at The Robert and Janice McNair Foundation (B.Z.). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research. BZ is a CPRIT Scholar in Cancer Research and a McNair scholar.
B.Z. received consulting fee from AstraZeneca. The remaining author declares no competing interests.
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Wen, B., Zhang, B. PepQuery2 democratizes public MS proteomics data for rapid peptide searching. Nat Commun 14, 2213 (2023). https://doi.org/10.1038/s41467-023-37462-4
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domain: literature


The NHL Draft and draft lottery are still months away, but the Montreal Canadiens look more and more destined for best odds at the No. 1 pick after losing what many called the "disaster bowl" against the Arizona Coyotes, and NHL Central Scouting is starting to release lists ranking the available prospects.
With that in mind, here's an update on all things NHL prospects in my latest notebook:
Men of Steel
The 10th edition of the BioSteel All-American game took place Monday in Plymouth, Michigan and Team Blue defeated Team White 4-3 in overtime. It was the most tightly contested game in the history of the event as USA Hockey has tweaked the format over the last few years. The current format, where USNTDP team players and the top draft-eligible players from the USHL were pooled together and then divided into two teams, seems to provide the most competitive environment.
Green Bay’s Damien Carfagna scored the game-winner. Program players Cutter Gauthier and Rutger McGroarty, both of Team Blue, led the way with two points each. McGroarty was named the Player of the Game.
Last week, NHL Central Scouting released its first numbered rankings for the 2022 NHL Draft.


Cotton South Africa (Cotton SA) has become the first laboratory to be certified under the ICA Bremen ‘International Laboratory Certification Scheme’.
Designed to raise the bar in the quality testing arena, the aim of the scheme is to establish an approved list of laboratories worldwide that meet a standard level of quality assurance.
On receiving the news, Gert Klindt, Quality Control Manager at Cotton SA said: “The Quality Control Division of Cotton South Africa is proud and honoured to become the first ICA Bremen certified laboratory. With our long standing history of classing and HVI fibre testing experience, we will endeavour to uphold the proud standard level of quality assurance within the international cotton environment as well as the aims and contract sanctity values of ICA Bremen.”
Following Cotton SA’s certification, Axel Drieling of the Bremen Fibre Institute (FIBRE), said: “Cotton SA is very experienced in cotton classing and testing, being not only responsible for the country’s cotton production, but also testing for other countries in the region. Its certification is of great significance, proving the laboratory is taking the necessary actions to retain and improve its performance.”
ICA Bremen has developed the scheme based on our own laboratory experience, as well as the good practices of the USDA (US Department of Agriculture), CSITC (Commercial Standardization of Instrument Testing of Cotton) and ASTM (American Society for Testing and Materials) and Axel believes it will bring significant benefits to the cotton trade: “For a laboratory, certification represents credibility and competence plus recognition and competitive advantage. For the global cotton community, the scheme gives the end user confidence in choosing a certified laboratory, as well as offering them more choice.”
Open to any international cotton testing laboratory, participating laboratories have to meet a level of quality assurance based on eight specific criteria, including conditioning, maintenance, calibration and testing procedures.
Eleven laboratories are currently in the process of assessment. Once certified, they will become a ‘laboratory of choice’ to resolve quality disputes in line with the ICA Bylaws & Rules, as well as providing a service to the cotton industry.


text:
If you love dreamsicles (orange and cream popsicles) then you’ll love this recipe. This frosting turns a simple yellow cake into a conversation piece when pillowed with this orangey goodness.
This recipe is from The Good Housekeeping Cookbook 125th Anniversary edition cookbook, as is the Simple Yellow Cake recipe. Make sure that your oranges are not too tart. I used quite a sweet navel orange and it tasted incredible. You can also substitute a lemon for the orange to make a lemony frosting.
- 1 lb or 500 g confectioners’ sugar (also known as powdered or icing sugar) Make sure you have a bit extra as depending on how soft the butter is when you start you make need to add more sugar as you go to get the right consistency
- 1/2 cup unsalted butter, softened
- Grated peel of one orange
- Juice of one orange (make sure it is sweet and not too tart)
1. Put the butter in a large mixing bowl adding a bit of sugar at a time. Beat together slowly or the sugar will puff up and coat everything in your kitchen in a fine, snowy dust. Using a shield and/or a tea towel helps keep the dust down.
2. Grate the orange peel, careful not to grate down through the white bitter pith, and add to the sugar and butter mixture.
3. Roll the orange to release the juice, cut in half and squeeze into the frosting mixture. If your orange has seeds, squeeze the juice into a bowl then remove the seeds before adding to the mixture.
4. Add extra sugar if needed until the frosting is stable but easily spreadable.
5. Pillow onto your cake (try this Simple Yellow Cake) and spread into a rustic but beautiful mess.

domain: food


text: I'll tell you what I liked the most about this confession: her willingness to taste something different! She found out about something that'd turn her on and jumped entirely in it to explore whatever would feel good. Fun and inspiring! This idea, plus my two fantastic (and sensual!) performers Tiffany Doll and Jay Smooth, made for a memorable film. I can only hope it inspires you too!

domain: artistic


St Mark’s Square in Venice empty after Italy’s first lockdown in the spring to curb the spread of … [+] COVID-19.
Rebecca Ann Hughes
Italy’s spring lockdown, one of the longest and strictest in Europe, gifted extraordinary experiences and photos of the country’s iconic tourist attractions devoid of people. As Italy’s latest COVID rules see regional borders closing and international travel continues to be restricted, these tourist hotspots are once more emptying. The situation is bittersweet. Many businesses, particularly those dependent on tourism, wonder if they’ll manage to survive a second travel hiatus. But with a full lockdown not yet imposed, it’s a unique opportunity for residents to reclaim the city for themselves.
Venice Falls Silent
Once poster-girl for overtourism, the canal city of Venice was suddenly the domain of locals for several months this spring. Even at the height of summer, continuing travel restrictions preventing tourism from countries like America and China meant the city was still a radically different place from previous years. Now, areas of the city previously lost to crushing crowds of tourists are clearing again.
Roberto Ferronato, chef de rang at the historic Caffè Florian, has observed Venice’s most iconic spot, St Mark’s Square, throughout these months. As he waits at the cafè’s tables set out in the square, he has been witness to its extraordinary emptiness. “In the city, at this moment, there are very few tourists,” Ferronato confirms.


text:
Thundering Hooves 2.0 sounds more like a summer blockbuster than a jargon-heavy £50,000 arts consultants report.
The post-election landscape has generated much debate about Scotland's identity as a nation in terms of its wider position within the UK and Europe, with the SNP's seminal advance central to the direction and character of the dialogue.
Conservatives who tell you Scotland must never have another independence referendum are the same people, as often as not, who complain that voters have not had "a say" on Europe in 40 years.
EVEN if it has passed from your grasp I am sure you might still remember it, your youth.
Sunday morning and I'm in church.
Slumbering, mouth open, gently drooling in the first of our hot, hot days, I awoke with a start at the sound of a car turning into the drive.
COME the revolution it will be heels against the wall.
"MANY tweeps have bezzies and discuss cakeages.
It is only week one of their new jobs and Scotland's rookie MPs have grabbed the headlines in the national as well as the Scottish press.
While the outcome of the General Election may have delivered a degree of short-term stability to our economic landscape, it is far from clear what impact a Conservative majority combined with the unprecedented numbers of SNP MPs at Westminster will mean in terms of taxation and the wider economy north of the Border.
THERE are testing times ahead for Scottish education.
An extraordinary event held at Glasgow City Chambers by the charity Roshni last night caused barely a public ripple, but should have done.
THIS is the best of times for our fellow citizens who happen not to be heterosexual, with a series of developments in these islands and across the continent occurring at breakneck pace.
Where bank scandals are concerned, the City euphemism is "reputational damage", as though someone's corporate paintwork has been chipped a little.
How many Labour leaders have won elections since the Second World War?

domain: news


text:
Quebec premier says bars could close following recent increase in COVID-19 cases
Compliance & Enforcement Health & Safety COVID-19 Quebec Testing
Province reported 142 new cases of coronavirus on Thursday
MONTREAL — Quebec Premier Francois Legault said Thursday he is concerned by the rise in COVID-19 infections as the province reported the highest single-day increase in confirmed cases since mid-June.
Legault said the province’s director of public health is analyzing the situation and will make a recommendation soon about whether to close bars and nightclubs following a recent string of outbreaks in the Montreal area linked to those venues.
“At this moment, we haven’t ruled out closing the bars,” Legault told reporters in Carleton, Que., in the Gaspesie region.
Quebec reported 142 new cases of COVID-19 Thursday — the largest single-day increase since June 12 — and 10 new deaths, nine of which occurred in the past 24 hours. The province has now reported a total of 57,001 COVID-19 cases and 5,646 deaths since the pandemic began.
Hospitalizations continue to drop in the province, however. The number of patients being treated in hospital fell by eight, for a total of 277, including 20 people who are in intensive care, the same number as Wednesday.
Testing capacity to increase
Authorities said they conducted 12,887 COVID-19 tests Tuesday, the last day for which data is available.
The rise in infections comes after authorities recently identified at least 30 cases of COVID-19 linked to nine Montreal-area bars, prompting health officials last weekend to instruct anyone who had gone to a bar in the city since July 1 to get tested.
Quebec last week tried to reduce COVID-19 exposure at bars by mandating the venues limit capacity to 50 per cent and stop serving alcohol at midnight.
“We tightened the rules,” Legault said Thursday. “But yes, I have concerns.”
The government was criticized this week after people said they had to wait several hours to be tested for COVID-19 at drop-in medical centres in Montreal.
Quebec said late Wednesday it would increase testing capacity in the city by 1,000 additional tests per day to meet demand.


text:
Tom al Ron - Rum Soaked Cheese
Tomme-style cheese soaked in Venezuelan Rum.
The oldest cheese of our range - Unique natural rinded cheese, full of flavour and character. Delivers a nice and delicate hint of the famous Venezuelan Diplomatico rum, producing floral/frutty notes.
It is inspired by some of the amazing European Alpine cheeses. Aged fora minimum of 6 months.
Ingredients: Pasteurised milk, salt, Venezuelan rum, non-animal rennet, cultures (starter & ripening cultures).
Allergy Advice: Contains milk.
In order to guarantee the quality of our products, we only ship through Express Post and dispatch days are Monday to Wednesday to avoid extended transit times. We recommend that all products are refrigerated on arrival.


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Will Ship in 3-5 Business Days.
2024 Cobra CX50 King Motorcycle
For the more advanced riders looking to dominate the track, the CX50SR King offersunrivaled power and agility. With a race-inspired design, this model boasts anupgraded engine, and enhanced suspension components, delivering exceptionalperformance and maneuverability. The CX50SR King is the recommended step upfrom our CX50JR.


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CityNews Article Archive:
Royal Park Rajapruek Invites Tourists to Join the Eco & Adventure Project 2012 from 14th – 16th September
CityNews – The upper northern region of Thailand including Chiang Mai, Lamphun and Mae Hong Son invites people to come to ‘Eco & Adventure 2012’ project from 14th – 16th September at Royal Park Rajapruek.
There will be over 40 booths with special promotions at the project, a seminar entitled ‘Road to AEC 2015: The Opportunity and The Challenges of Eco & Adventure Toursim in Northern Thailand, a tourism exhibition, adventure tourism demonstrations featuring camping, hiking, ATV riding and canoeing.
Jurirat Praewprai, the director of Office of Tourism and Sport Chiang Mai said ‘Eco & Adventure 2012’ would motivate tourists to visit Chiang Mai to enjoy eco and adventure tourism in the low season.
Eco & Adventure 2012 ? Green Season
? 1 ? ? ? ? ?“? 2012” ? 14-16 ? 2555 ? ? ? ? Hub Eco &Adventure ? ? Green Season ? ? 40 ? “? AEC 2015: ?” ?,? ? ? ? ? ? ? ATV ?
? ? ? ?1(?,?,?)? “? 2012” ? 1 ? 2555 ? 14-16 ? 2555 ? ? ?.? ? ? 1 ? ? ? 1?

domain: travel


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Inspiration and Ideas
Tips & Tricks
"You can't buy a jar of pickles that tastes like this, and it just doesn't get much easier to mix up a batch." – lutzflcat
Homemade Refrigerator Pickles
Watch how to make these Homemade Refrigerator Pickles.
Refrigerator Dill Pickles
"Excellent, simple recipe! I used 5 small pickling cucumbers and they turned out perfect, even after only 1 day in the fridge. This is my new go-to pickle recipe!" – LilSnoo


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Saturday, October 5, 2013
Ever been in school or in scouting and learned a very silly song, usually with some hand movements or other physical form of expression that was super silly but also a lot of fun?
Though I couldn't remember what it was, I know I've done them.
Cecilia's and Felicity's unit learned a song and dance called Tooty Ta, a silly song written by Dr. Jean Feldman who is an early childhood educator and musician. I didn't catch the whole thing on video, but I got the second half....
Felicity is just left of the center of the screen and Cecilia is closer but further left than Felicity in the blue crocs.

domain: entertainment


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At least 100 organisations, many of them obscure, will unite to protest against the National Population Register(NPR), National Register of Citizens(NRC) and the enactment of the Citizenship Amendment Act, said the Swaraj Abhiyan Party President Yogendra Yadav at a national coordination committee meeting held in TISS on Monday.
The discussion which was held to chart the future course of action regarding protests against the Citizenship Amendment Act (CAA) was attended by Rashtriya Seva Dal President Ganesh Devi, student leader Kanhaiya Kumar, United Against Hate member Umar Khalid, Kavita Krishnan, Medha Patkar and the controversial activist Harsh Mander, known for constituting skewed hate-tracker.
According to Yadav, the meeting saw participation from about 100 organisations across the country during which a month-long campaign was planned to be held across the country, under the banner ‘We The People of India’. The organisers asked all the protestors to hold protests under the same banner-which is also the first four words of the Indian Constitution.
As of now, at least six national-level protests have been planned to happen in the month of January. The first protest is intended to happen on Savitribai Phule Divas, January 3, 2020. The next protest is a planned Bharat Bandh on January 8. The third protest is envisaged on the Youth Day (January 12) while the fourth one is planned on the death anniversary of Rohith Vemula/social justice day (January 17). Fifth and sixth protests will be held on January 26(Republic Day) and January 30(Mahatma Gandhi’s death anniversary).
Accusing the government of repressing the voice of the people in connection with the recent clampdown on the rioters by the police in different parts of the country, Yadav asserted that the protest will entail a call for a boycott of NRC, NPR and CAA by the participating organisations. He also added that a request will be made to the government to declare their intentions regarding the implementation of the NRC in a standard formalised manner.


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New International Version
When you have eaten and are satisfied, praise the LORD your God for the good land he has given you.
King James Bible
When thou hast eaten and art full, then thou shalt bless the LORD thy God for the good land which he hath given thee.
Darby Bible Translation
And thou shalt eat and be filled, and shalt bless Jehovah thy God for the good land which he hath given thee.
World English Bible
You shall eat and be full, and you shall bless Yahweh your God for the good land which he has given you.
Young's Literal Translation
and thou hast eaten, and been satisfied, and hast blessed Jehovah thy God, on the good land which he hath given to thee.
Deuteronomy 8:10 Parallel
CommentaryClarke's Commentary on the Bible
A land whose stones are iron - Not only meaning that there were iron mines throughout the land, but that the loose stones were strongly impregnated with iron, ores of this metal (the most useful of all the products of the mineral kingdom) being every where in great plenty.
Out of whose hills thou mayest dig brass - As there is no such thing in nature as a brass mine, the word נחשת nechosheth should be translated copper; of which, by the addition of the lapis calaminaris, brass is made. See on Exodus 25:3 (note).
Treasury of Scripture Knowledge
DEUTERONOMY viii. 2-5. And thou shalt remember all the way which the Lord thy God led thee these forty years in the wilderness, to humble thee, and to prove thee, to know what was in thine heart, whether thou wouldest keep his commandments or no. And he humbled thee, and suffered thee to hunger, and fed thee with manna, which thou knewest not, neither did thy fathers know; that he might make thee know that man doth not live by bread only, but by every word that proceedeth out of the mouth of the …
Charles Kingsley—Discipline and Other Sermons
Subterraneous Places. Mines. Caves.
Meditations Before Dinner and Supper.
Third Sunday Before Lent
houses filled with all kinds of good things you did not provide, wells you did not dig, and vineyards and olive groves you did not plant--then when you eat and are satisfied,
a land where bread will not be scarce and you will lack nothing; a land where the rocks are iron and you can dig copper out of the hills.
When I have brought them into the land flowing with milk and honey, the land I promised on oath to their ancestors, and when they eat their fill and thrive, they will turn to other gods and worship them, rejecting me and breaking my covenant.
Jump to PreviousBless Blessed Eat Eaten Enough Praise Praising Satisfied You
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If you've been wondering how the Marlins started scoring runs all of a sudden, and especially at Marlins Park, one of the best pitcher's parks in the majors, you're not alone. The Atlanta Braves found it more than just a little suspicious that the Marlins were not only tearing it up in their home park, but going hog wild against Aaron Harang on Wednesday just days after striking out 11 times against him in Atlanta.
The Braves, in fact, began to wonder if the Marlins were up to no good, specifically, by stealing signs through the use of cameras positioned strategically around the ballpark. That's right. The Braves wondered if the Marlins had concealed a camera inside the Home Run Sculpture. Braves pitching coach Roger McDowell even threw a towel over a Fox Sports camera lens before Thursday's game to keep it from focusing in on Braves starter Ervin Santana as he was warming up in the bullpen.
From the Atlanta Journal-Constitution:
"If you would have taken a look at our dugout at one point in the game, it was like the fourth or fifth inning, they were hitting balls everywhere, we got three guys looking at the scoreboard,” (Braves manager Fredi) Gonzalez said. “You got two guys looking at their bullpen. I’m calling (bullpen coach) Eddie (Perez), ‘Eddie do you see anything?’ I’m looking at Gattis, thinking he’s maybe tipping his pitches. Carlos (Tosca) is looking in the bench over there, maybe somebody is whistling or something.”
Gonzalez said he changed signs five times during the course of Harang’s outing and went to multiple signs even with no runners on base. The hits kept coming regardless.
Gonzalez said he wondered if Gattis was giving away signs, but then figured that wouldn’t account for the disparity in the Marlins home/road splits in general. Entering play Thursday, the Marlins were hitting .307 while scoring 6.3 runs per game at Marlins Park. They were hitting .215 with 2.7 runs per game on the road.
“Yeah, you have this conspiracy theory, but at the end, we came up with nothing,” Gonzalez said. “It wasn’t like we saw a guy with the (binoculars), like Mick Billmeyer (former Phillies bullpen coach) in Colorado. At the end of the day, they didn’t miss the pitches. They were right there.”
Gonzalez was laughing when he told the story Thursday afternoon in the Braves dugout, describing how the Braves went so far as to look at the sculpture in left center field, wondering if there was somebody hiding in there with a camera.
“There was one guy sitting (in outfield seats) who had a red hat and an orange shirt,” Gonzalez said. “I said ‘Boy that’s a bad combination to have. I told (Jordan) Schafer and (Tyler) Pastornicky to keep an eye on that guy over there.’ The guy got up, went to get a coke.”
The Marlins, fresh off a series sweep over the Braves for the first time in five seasons, denied any such shenanigans.
"Just give us a little credit," said Marlins manager Mike Redmond. "I mean, we're out there playing the game the right way. Guys are battling and competing. That's how we're winning ballgames. Actually, I don't even think much about it because my focus is on our guys and my team and what we're doing. We just played a great three-game series and I'm not going to let anything diminish that."
Marlins third baseman Casey McGehee chuckled when asked about the Braves' suspicions. He said when he was with Milwaukee, the Brewers were often accused of stealing signs because of their tilted home/road splits.
If the Brewers were stealing signs through the use of an outfield camera, McGehee laughed and said "I would have hoped they told me before I hit .220."
"I'm not going to say it's never happened in the history of the game before," McGehee said. "But we're not splitting any atoms, let's put it that way."


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When singer-songwriter Tim Flannery plays guitar, he needs to take off his jewelry. Otherwise his three World Series rings might cramp his style. Flannery spent eleven seasons as a fan favorite with the San Diego Padres and eight as third base coach for the San Francisco Giants, where he called runners in to home plate on the way to three World Series wins.
Now retired from baseball, Flannery spends much of his time with his band The Lunatic Fringe, in which Studio West’s own Shawn Rohlf serves as a multi-instrumentalist “utility man,” playing instruments including banjo, mandolin, bass, and electric and acoustic guitars.
Flannery, as you can imagine, has plenty of stories after 34 years in professional baseball and playing music with the likes of Jackson Browne, Bruce Hornsby, Garth Brooks and Jerry Jeff Walker. Last week Comcast Sports in the Bay Area gave Flannery a half-hour slot to tell those tales with a new show called Songs and Stories. The show also features Tim, Shawn and the rest of The Lunatic Fringe playing their soulful tunes. And to keep it all in the Studio West family, our own audio engineer Ben Hasdovic mastered the show’s audio tracks.
Although Songs and Stories isn’t yet available online, check out the video of Shawn and Tim in Studio A performing “San Francisco Love Affair”—one of Shawn’s songs featured on Songs and Stories that has become a favorite in the Bay Area.


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