Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance.

Introduction: The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or "California COVIDNet". This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. Methods: California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. Results: Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. Discussion: Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.

TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization.

Introduction: The clinical incidence of antimicrobial-resistant fungal infections has dramatically increased in recent years. Certain fungal pathogens colonize various body cavities, leading to life-threatening bloodstream infections. However, the identification and characterization of fungal isolates in laboratories remain a significant diagnostic challenge in medicine and public health. Whole-genome sequencing provides an unbiased and uniform identification pipeline for fungal pathogens but most bioinformatic analysis pipelines focus on prokaryotic species. To this end, TheiaEuk_Illumina_PE_PHB (TheiaEuk) was designed to focus on genomic analysis specialized to fungal pathogens. Methods: TheiaEuk was designed using containerized components and written in the workflow description language (WDL) to facilitate deployment on the cloud-based open bioinformatics platform Terra. This species-agnostic workflow enables the analysis of fungal genomes without requiring coding, thereby reducing the entry barrier for laboratory scientists. To demonstrate the usefulness of this pipeline, an ongoing outbreak of C. auris in southern Nevada was investigated. We performed whole-genome sequence analysis of 752 new C. auris isolates from this outbreak. Furthermore, TheiaEuk was utilized to observe the accumulation of mutations in the FKS1 gene over the course of the outbreak, highlighting the utility of TheiaEuk as a monitor of emerging public health threats when combined with whole-genome sequencing surveillance of fungal pathogens. Results: A primary result of this work is a curated fungal database containing 5,667 unique genomes representing 245 species. TheiaEuk also incorporates taxon-specific submodules for specific species, including clade-typing for Candida auris (C. auris). In addition, for several fungal species, it performs dynamic reference genome selection and variant calling, reporting mutations found in genes currently associated with antifungal resistance (FKS1, ERG11, FUR1). Using genome assemblies from the ATCC Mycology collection, the taxonomic identification module used by TheiaEuk correctly assigned genomes to the species level in 126/135 (93.3%) instances and to the genus level in 131/135 (97%) of instances, and provided zero false calls. Application of TheiaEuk to actual specimens obtained in the course of work at a local public health laboratory resulted in 13/15 (86.7%) correct calls at the species level, with 2/15 called at the genus level. It made zero incorrect calls. TheiaEuk accurately assessed clade type of Candida auris in 297/302 (98.3%) of instances. Discussion: TheiaEuk demonstrated effectiveness in identifying fungal species from whole genome sequence. It further showed accuracy in both clade-typing of C. auris and in the identification of mutations known to associate with drug resistance in that organism.

Accelerating bioinformatics implementation in public health.

We have adopted an open bioinformatics ecosystem to address the challenges of bioinformatics implementation in public health laboratories (PHLs). Bioinformatics implementation for public health requires practitioners to undertake standardized bioinformatic analyses and generate reproducible, validated and auditable results. It is essential that data storage and analysis are scalable, portable and secure, and that implementation of bioinformatics fits within the operational constraints of the laboratory. We address these requirements using Terra, a web-based data analysis platform with a graphical user interface connecting users to bioinformatics analyses without the use of code. We have developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners. These Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology. Additonally, these workflows use open-source containerized software and the WDL workflow language to ensure standardization and interoperability with other bioinformatics solutions, whilst being adaptable by the user. They are all open source and publicly available in Dockstore with the version-controlled code available in public GitHub repositories. They have been written to generate outputs in standardized file formats to allow for further downstream analysis and visualization with separate genomic epidemiology software. Testament to this solution meeting the requirements for bioinformatic implementation in public health, Theiagen workflows have collectively been used for over 5 million sample analyses in the last 2 years by over 90 public health laboratories in at least 40 different countries. Continued adoption of technological innovations and development of further workflows will ensure that this ecosystem continues to benefit PHLs.

The use of whole-genome sequencing and development of bioinformatics to monitor overlapping outbreaks of Candida auris in southern Nevada.

A Candida auris outbreak has been ongoing in Southern Nevada since August 2021. In this manuscript we describe the sequencing of over 200 C. auris isolates from patients at several facilities. Genetically distinct subgroups of C. auris were detected from Clade I (3 distinct lineages) and III (1 lineage). Open-source bioinformatic tools were developed and implemented to aid in the epidemiological investigation. The work herein compares three methods for C. auris whole genome analysis: Nullarbor, MycoSNP and a new pipeline TheiaEuk. We also describe a novel analysis method focused on elucidating phylogenetic linkages between isolates within an ongoing outbreak. Moreover, this study places the ongoing outbreaks in a global context utilizing existing sequences provided worldwide. Lastly, we describe how the generated results were communicated to the epidemiologists and infection control to generate public health interventions.

Pathogen genomics in public health laboratories: successes, challenges, and lessons learned from California's SARS-CoV-2 Whole-Genome Sequencing Initiative, California COVIDNet.

The capacity for pathogen genomics in public health expanded rapidly during the coronavirus disease 2019 (COVID-19) pandemic, but many public health laboratories did not have the infrastructure in place to handle the vast amount of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequence data generated. The California Department of Public Health, in partnership with Theiagen Genomics, was an early adopter of cloud-based resources for bioinformatics and genomic epidemiology, resulting in the creation of a SARS-CoV-2 genomic surveillance system that combined the efforts of more than 40 sequencing laboratories across government, academia and industry to form California COVIDNet, California's SARS-CoV-2 Whole-Genome Sequencing Initiative. Open-source bioinformatics workflows, ongoing training sessions for the public health workforce, and automated data transfer to visualization tools all contributed to the success of California COVIDNet. While challenges remain for public health genomic surveillance worldwide, California COVIDNet serves as a framework for a scaled and successful bioinformatics infrastructure that has expanded beyond SARS-CoV-2 to other pathogens of public health importance.

Genomic surveillance of Nevada patients revealed prevalence of unique SARS-CoV-2 variants bearing mutations in the RdRp gene.

Patients with signs of COVID-19 were tested through diagnostic RT-PCR for SARS-CoV-2 using RNA extracted from the nasopharyngeal/nasal swabs. To determine the variants of SARS-CoV-2 circulating in the state of Nevada, specimens from 200 COVID-19 patients were sequenced through our robust sequencing platform, which enabled sequencing of SARS-CoV-2 from specimens with even very low viral loads, without the need of culture-based amplification. High genome coverage allowed the identification of single and multi-nucleotide variants in SARS-CoV-2 in the community and their phylogenetic relationships with other variants present during the same period of the outbreak. We report the occurrence of a novel mutation at 323aa (314aa of orf1b) of nsp12 (RNA-dependent RNA polymerase) changed to phenylalanine (F) from proline (P), in the first reported isolate of SARS-CoV-2, Wuhan-Hu-1. This 323F variant was present at a very high frequency in Northern Nevada. Structural modeling determined this mutation in the interface domain, which is important for the association of accessory proteins required for the polymerase. In conclusion, we report the introduction of specific SARS-CoV-2 variants at very high frequency in distinct geographic locations, which is important for understanding the evolution and circulation of SARS-CoV-2 variants of public health importance, while it circulates in humans.

Genomic evidence for reinfection with SARS-CoV-2: a case study.

BACKGROUND: The degree of protective immunity conferred by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently unknown. As such, the possibility of reinfection with SARS-CoV-2 is not well understood. We describe an investigation of two instances of SARS-CoV-2 infection in the same individual. METHODS: A 25-year-old man who was a resident of Washoe County in the US state of Nevada presented to health authorities on two occasions with symptoms of viral infection, once at a community testing event in April, 2020, and a second time to primary care then hospital at the end of May and beginning of June, 2020. Nasopharyngeal swabs were obtained from the patient at each presentation and twice during follow-up. Nucleic acid amplification testing was done to confirm SARS-CoV-2 infection. We did next-generation sequencing of SARS-CoV-2 extracted from nasopharyngeal swabs. Sequence data were assessed by two different bioinformatic methodologies. A short tandem repeat marker was used for fragment analysis to confirm that samples from both infections came from the same individual. FINDINGS: The patient had two positive tests for SARS-CoV-2, the first on April 18, 2020, and the second on June 5, 2020, separated by two negative tests done during follow-up in May, 2020. Genomic analysis of SARS-CoV-2 showed genetically significant differences between each variant associated with each instance of infection. The second infection was symptomatically more severe than the first. INTERPRETATION: Genetic discordance of the two SARS-CoV-2 specimens was greater than could be accounted for by short-term in vivo evolution. These findings suggest that the patient was infected by SARS-CoV-2 on two separate occasions by a genetically distinct virus. Thus, previous exposure to SARS-CoV-2 might not guarantee total immunity in all cases. All individuals, whether previously diagnosed with COVID-19 or not, should take identical precautions to avoid infection with SARS-CoV-2. The implications of reinfections could be relevant for vaccine development and application. FUNDING: Nevada IDEA Network of Biomedical Research, and the National Institute of General Medical Sciences (National Institutes of Health).

Genomic surveillance of Nevada patients revealed prevalence of unique SARS-CoV-2 variants bearing mutations in the RdRp gene.

Patients with signs of COVID-19 were tested with CDC approved diagnostic RT-PCR for SARS-CoV-2 using RNA extracted from nasopharyngeal/nasal swabs. In order to determine the variants of SARS-CoV-2 circulating in the state of Nevada, 200 patient specimens from COVID-19 patients were sequenced through our robust protocol for sequencing SARS-CoV-2 genomes. Our protocol enabled sequencing of SARS-CoV-2 genome directly from the specimens, with even very low viral loads, without the need of culture-based amplification. This allowed the identification of specific nucleotide variants including those coding for D614G and clades defining mutations. These sequences were further analyzed for determining SARS-CoV-2 variants circulating in the state of Nevada and their phylogenetic relationships with other variants present in the united states and the world during the same period of the outbreak. Our study reports the occurrence of a novel variant in the nsp12 (RNA dependent RNA Polymerase) protein at residue 323 (314aa of orf1b) to Phenylalanine (F) from Proline (P), present in the original isolate of SARS-CoV-2 (Wuhan-Hu-1). This 323F variant is found at a very high frequency (46% of the tested specimen) in Northern Nevada. Functional significance of this unique and highly prevalent variant of SARS-CoV-2 with RdRp mutation is currently under investigation but structural modeling showed this 323aa residue in the interface domain of RdRp, which is required for association with accessory proteins. In conclusion, we report the introduction of specific SARS-CoV-2 variants at a very high frequency within a distinct geographic location, which is important for clinical and public health perspectives in understanding the evolution of SARS-CoV-2 while in circulation.

Proteomic analysis reveals virus-specific Hsp25 modulation in cardiac myocytes.

Viruses frequently infect the heart but clinical myocarditis is rare, suggesting that the cardiac antiviral response is uniquely effective. Indeed, the Type I interferon (IFN) response is cardiac cell-type specific and provides one integrated network of protection for the heart. Here, a proteomic approach was used to identify additional proteins that may be involved in the cardiac antiviral response. Reovirus-induced murine myocarditis reflects direct viral damage to cardiac cells and offers an excellent system for study. Primary cultures of murine cardiac myocytes were infected with myocarditic or nonmyocarditic reovirus strains, and whole cell lysates were compared by two-dimensional difference gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF/TOF) tandem mass spectrometry. Results were quantitative and reproducible and demonstrated that whole proteome changes clustered according to viral pathogenic phenotype. Moreover, the data suggest that the heat shock protein Hsp25 is modulated differentially by myocarditic and nonmyocarditic reoviruses and may play a role in the cardiac antiviral response. Members of seven virus families modulate Hsp25 or Hsp27 expression in a variety of cell types, suggesting that Hsp25 participation in the antiviral response may be widespread. However, results here provide the first evidence for a virus-induced decrease in Hsp25/27 and suggest that viruses may have evolved a mechanism to subvert this protective response, as they have for IFN.

Systematic comparison of the human saliva and plasma proteomes.

The proteome of human salivary fluid has the potential to open new doors for disease biomarker discovery. A recent study to comprehensively identify and catalog the human ductal salivary proteome led to the compilation of 1166 proteins. The protein complexity of both saliva and plasma is large, suggesting that a comparison of these two proteomes will provide valuable insight into their physiological significance and an understanding of the unique and overlapping disease diagnostic potential that each fluid provides. To create a more comprehensive catalog of human salivary proteins, we have first compiled an extensive list of proteins from whole saliva (WS) identified through MS experiments. The WS list is thereafter combined with the proteins identified from the ductal parotid, and submandibular and sublingual (parotid/SMSL) salivas. In parallel, a core dataset of the human plasma proteome with 3020 protein identifications was recently released. A total of 1939 nonredundant salivary proteins were compiled from a total of 19 474 unique peptide sequences identified from whole and ductal salivas; 740 out of the total 1939 salivary proteins were identified in both whole and ductal saliva. A total of 597 of the salivary proteins have been observed in plasma. Gene ontology (GO) analysis showed similarities in the distributions of the saliva and plasma proteomes with regard to cellular localization, biological processes, and molecular function, but revealed differences which may be related to the different physiological functions of saliva and plasma. The comprehensive catalog of the salivary proteome and its comparison to the plasma proteome provides insights useful for future study, such as exploration of potential biomarkers for disease diagnostics.

Proteomics of Pyrococcus furiosus, a hyperthermophilic archaeon refractory to traditional methods.

Pyrococcus furiosus is one of the most extensively studied hyperthermophilic archaea. Proteins from this hyperthemophile organism are extremely thermostable and are highly resistant to chemical denaturants, organic solvents and proteolytic digestion. This thermostability makes it difficult to apply traditional methods of enzymatically digesting a complex mixture of proteins, commonly a first step in peptide generation in most shotgun proteomics methods. Here, we have developed a simple shotgun proteomics approach for the global identification of the P. furiosus proteome. This methodology uses a detergent-based microwave assisted acid hydrolysis (MAAH) step coupled with an overnight trypsin digest to obtain peptides. Subsequent peptide fractionation by isoelectric focusing in immobilized pH gradients (IPG-IEF), followed by chromatographic separation with reverse phase nano-HPLC and electrospray ionization tandem mass spectrometry (ESI-MS/MS) of peptides enabled the identification of over 900 proteins representing over 44% of the proteome. In most functional classes, over 50% of the predicted proteins were identified, including a number of membrane proteins. This new sample preparation technique will enable extensive proteomics data to be obtained for this organism, thereby enabling the reconstruction of metabolic pathways and promoting a systems biology based understanding of this important extremophile.

Calculation of the isoelectric point of tryptic peptides in the pH 3.5-4.5 range based on adjacent amino acid effects.

Current algorithms for the calculation of peptide or protein pI, based on the charge associated with individual amino acids, can calculate pI values to within +/-0.2 pI units. Here, we present a new pI calculation algorithm that takes into account the effect of adjacent amino acids on the pI value. The algorithm accounts for the effect of adjacent amino acids+/-3 residues away from a charged aspartic or glutamic acid, as well as effects on the free C terminus, and applies a correction term to the corresponding pK values. The correction increments are derived from a 5000-peptide training set using a genetic optimization approach. The accuracy of the new pI values obtained with this method approaches the error associated with the manufacture of the IPG strip (<+/-0.03 pI units). The approach is demonstrated for cytosolic cell extracts derived from the breast-cancer cell line DU4475, and from membrane preparations from human lung-tissue samples. One potential application of a more highly accurate pI calculation is data filtering of MS/MS outputs that will allow for more complex database searches including gene finding, and validation, and detection of coding single-nucleotide polymorphisms in their expressed form.

Whole genome searching with shotgun proteomic data: applications for genome annotation.

High-throughput genome sequencing continues to accelerate the rate at which complete genomes are available for biological research. Many of these new genome sequences have little or no genome annotation currently available and hence rely upon computational predictions of protein coding genes. Evidence of translation from proteomic techniques could facilitate experimental validation of protein coding genes, but the techniques for whole genome searching with MS/MS data have not been adequately developed to date. Here we describe GENQUEST, a novel method using peptide isoelectric focusing and accurate mass to greatly reduce the peptide search space, making fast, accurate, and sensitive whole human genome searching possible on common desktop computers. In an initial experiment, almost all exonic peptides identified in a protein database search were identified when searching genomic sequence. Many peptides identified exclusively in the genome searches were incorrectly identified or could not be experimentally validated, highlighting the importance of orthogonal validation. Experimentally validated peptides exclusive to the genomic searches can be used to reannotate protein coding genes. GENQUEST represents an experimental tool that can be used by the proteomics community at large for validating computational approaches to genome annotation.

Detection and validation of non-synonymous coding SNPs from orthogonal analysis of shotgun proteomics data.

Orthogonal analysis of amino acid substitutions as a result of SNPs in existing proteomic datasets provides a critical foundation for the emerging field of population-based proteomics. Large-scale proteomics datasets, derived from shotgun tandem MS analysis of complex cellular protein mixtures, contain many unassigned spectra that may correspond to alternate alleles coded by SNPs. The purpose of this work was to identify tandem MS spectra in LC-MS/MS shotgun proteomics datasets that may represent coding nonsynonymous SNPs (nsSNP). To this end, we generated a tryptic peptide database created from allelic information found in NCBI's dbSNP. We searched this database with tandem MS spectra of tryptic peptides from DU4475 breast tumor cells that had been fractioned by pI in the first-dimension and reverse-phase LC in the second dimension. In all we identified 629 nsSNPs, of which 36 were of alternate SNP alleles not found in the reference NCBI or IPI protein databases. Searches for SNP-peptides carry a high risk of false positives due both to mass shifts caused by modifications and because of multiple representations of the same peptide within the genome. In this work, false positives were filtered using a novel peptide pI prediction algorithm and characterized using a decoy database developed by random substitution of similarly sized reference peptides. Secondary validation by sequencing of corresponding genomic DNA confirmed the presence of the predicted SNP in 8 of 10 SNP-peptides. This work highlights that the usefulness of interpreting unassigned spectra as polymorphisms is highly reliant on the ability to detect and filter false positives.

Minimizing back exchange in 18O/16O quantitative proteomics experiments by incorporation of immobilized trypsin into the initial digestion step.

Differential labeling of peptides via the use of the 18O-water proteolytic labeling method has been widely adopted for quantitative shotgun proteomics studies due to its simplicity and low reagent costs. In this report, the use of immobilized trypsin in the initial digestion step, in addition to the initial digestion step, is explored as a means to minimize postlabeling back exchange of 18O-labeled peptides into the 16O form when multidimensional peptide separation methods (here, isoelectric focusing of peptides) are incorporated into the sample workflow. Examples are shown with a mixture of standard proteins and a sample from an ongoing clinical proteomics study.

Analysis of membrane proteins from human chronic myelogenous leukemia cells: comparison of extraction methods for multidimensional LC-MS/MS.

An important strategy for "shotgun proteomics" profiling involves solution proteolysis of proteins, followed by peptide separation using multidimensional liquid chromatography and automated sequencing by mass spectrometry (LC-MS/MS). Several protocols for extracting and handling membrane proteins for shotgun proteomics experiments have been reported, but few direct comparisons of different protocols have been reported. We compare four methods for preparing membrane proteins from human cells, using acid labile surfactants (ALS), urea, and mixed organic-aqueous solvents. These methods were compared with respect to their efficiency of protein solubilization and proteolysis, peptide and protein recovery, membrane protein enrichment, and peptide coverage of transmembrane proteins. Overall, approximately 50-60% of proteins recovered were membrane-associated, identified from Gene Ontology annotations and transmembrane prediction software. Samples extracted with ALS, extracted with urea followed by dilution, or extracted with urea followed by desalting yielded comparable peptide recoveries and sequence coverage of transmembrane proteins. In contrast, suboptimal proteolysis was observed with organic solvent. Urea extraction followed by desalting may be a particularly useful approach, as it is less costly than ALS and yields satisfactory protein denaturation and proteolysis under conditions that minimize reactivity with urea-derived cyanate. Spectral counting was used to compare datasets of proteins from membrane samples with those of soluble proteins from K562 cells, and to estimate fold differences in protein abundances. Proteins most highly abundant in the membrane samples showed enrichment of integral membrane protein identifications, consistent with their isolation by differential centrifugation.

Incorporating expression data in metabolic modeling: a case study of lactate dehydrogenase.

Integrating biological information from different sources to understand cellular processes is an important problem in systems biology. We use data from mRNA expression arrays and chemical kinetics to formulate a metabolic model relevant to K562 erythroleukemia cells. MAP kinase pathway activation alters the expression of metabolic enzymes in K562 cells. Our array data show changes in expression of lactate dehydrogenase (LDH) isoforms after treatment with phorbol 12-myristate 13-acetate (PMA), which activates MAP kinase signaling. We model the change in lactate production which occurs when the MAP kinase pathway is activated, using a non-equilibrium, chemical-kinetic model of homolactic fermentation. In particular, we examine the role of LDH isoforms, which catalyse the conversion of pyruvate to lactate. Changes in the isoform ratio are not the primary determinant of the production of lactate. Rather, the total concentration of LDH controls the lactate concentration.

Comparison of label-free methods for quantifying human proteins by shotgun proteomics.

Measurements of mass spectral peak intensities and spectral counts are promising methods for quantifying protein abundance changes in shotgun proteomic analyses. We describe Serac, software developed to evaluate the ability of each method to quantify relative changes in protein abundance. Dynamic range and linearity using a three-dimensional ion trap were tested using standard proteins spiked into a complex sample. Linearity and good agreement between observed versus expected protein ratios were obtained after normalization and background subtraction of peak area intensity measurements and correction of spectral counts to eliminate discontinuity in ratio estimates. Peak intensity values useful for protein quantitation ranged from 10(7) to 10(11) counts with no obvious saturation effect, and proteins in replicate samples showed variations of less than 2-fold within the 95% range (+/-2sigma) when >or=3 peptides/protein were shared between samples. Protein ratios were determined with high confidence from spectral counts when maximum spectral counts were >or=4 spectra/protein, and replicates showed equivalent measurements well within 95% confidence limits. In further tests, complex samples were separated by gel exclusion chromatography, quantifying changes in protein abundance between different fractions. Linear behavior of peak area intensity measurements was obtained for peptides from proteins in different fractions. Protein ratios determined by spectral counting agreed well with those determined from peak area intensity measurements, and both agreed with independent measurements based on gel staining intensities. Overall spectral counting proved to be a more sensitive method for detecting proteins that undergo changes in abundance, whereas peak area intensity measurements yielded more accurate estimates of protein ratios. Finally these methods were used to analyze differential changes in protein expression in human erythroleukemia K562 cells stimulated under conditions that promote cell differentiation by mitogen-activated protein kinase pathway activation. Protein changes identified with p<0.1 showed good correlations with parallel measurements of changes in mRNA expression.

Immobilized pH gradient isoelectric focusing as a first-dimension separation in shotgun proteomics.

Shotgun proteomics, where a tryptic digest of a complex proteome sample is directly analyzed by either single dimensional or multidimensional liquid chromatography tandem mass spectrometry, has gained acceptance in the proteomics community at large and is widely used in core facilities. Here we review the development in our laboratory of an alternative first-dimension separation technique for shotgun proteomics, immobilized pH gradient isoelectric focusing (IPG-IEF). The key advantages of the technology over other multidimensional separation formats (simplicity, high resolution, and high sensitivity) are discussed. The concept of using peptide pI to filter large shotgun proteomics datasets generated by the IPG-IEF technique to minimize false positives and negatives is also introduced. Finally, an account of the comparison of the technique with the established gold standard for multidimensional separation of peptides, strong cation exchange chromatography, is presented, along with the prospects for the use of peptide pI along with accurate mass measurement for the identification of peptides.