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Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Conventional diagnostic tools for prostate cancer (PCa), such as prostate-specific antigen (PSA), transrectal ultrasound (TRUS), digital rectal examination (DRE), and tissue biopsy face, limitations in individual risk stratification due to invasiveness or reliability issues. Liquid biopsy is a less invasive and more accurate alternative. Metabolomic analysis of extracellular vesicles (EVs) holds a promise for detecting non-genetic alterations and biomarkers in PCa diagnosis and risk assessment. The current research gap in PCa lies in the lack of accurate biomarkers for early diagnosis and real-time monitoring of cancer progression or metastasis. Establishing a suitable approach for observing dynamic EV metabolic alterations that often occur earlier than being detectable by other omics technologies makes metabolomics valuable for early diagnosis and monitoring of PCa. Using four distinct metabolite extraction approaches, the metabolite cargo of PC3-derived large extracellular vesicles (lEVs) was evaluated using a combination of methanol, cell shearing using microbeads, and size exclusion filtration, as well as two fractionation chemistries (pHILIC and C18 chromatography) that are also examined. The unfiltered methanol-microbeads approach (MB-UF), followed by pHILIC LC-MS/MS for EV metabolite extraction and analysis, is effective. Identified metabolites such as L-glutamic acid, pyruvic acid, lactic acid, and methylmalonic acid have important links to PCa and are discussed. Our study, for the first time, has comprehensively evaluated the extraction and separation methods with a view to downstream sample integrity across omics platforms, and it presents an optimised protocol for EV metabolomics in PCa biomarker discovery.

Objectives: Pro-inflammatory molecules are thought to underpin the development of chronic low back pain (LBP). Although research has begun to explore the association between pro-inflammatory molecules in acute LBP and long-term outcome, no study has explored the role of anti-inflammatory molecules. We aimed to explore whether levels of systemic pro- and anti-inflammatory molecules 1) changed over a period of six months from the onset of acute LBP; 2) differed between people who were recovered (N = 11) and unrecovered (N = 24) from their episode of LBP at six months; 3) baseline psychological factors were related to inflammatory molecule serum concentrations at baseline, three and six months., Methods: We retrospectively included participants with acute LBP included from a larger prospective trial and examined blood samples for the measurement of pro- and anti-inflammatory molecules and measures of pain, disability, and psychological factors at baseline, three and six months., Results: The serum concentrations of pro- and anti-inflammatory molecules did not differ over time when compared between participants who recovered and those who did not recover at six-month follow-up. At three months, the unrecovered group had higher interleukin (IL)-8 and IL-10 serum concentrations than the recovered group. Baseline psychological factors were not related to inflammatory molecules at any time point., Discussion: This exploratory study showed that levels of systemic inflammatory molecules did not change over the course of LBP, irrespective of whether people were recovered or unrecovered at six months. There was no relationship between acute-stage psychological factors and systemic inflammatory molecules. Further investigation is needed to elucidate the contribution of pro- and anti-inflammatory molecules to long-term LBP outcome., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Chang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Crohn's disease and ulcerative colitis are common chronic idiopathic inflammatory bowel diseases (IBD), which cause considerable morbidity. Although the precise mechanisms of disease remain unclear, evidence implicates a strong multidirectional interplay between diet, environmental factors, genetic determinants/immune perturbations and the gut microbiota. IBD can be brought into remission using a number of medications, which act by suppressing the immune response. However, none of the available medications address any of the underlying potential mechanisms. As we understand more about how the microbiota drives inflammation, much interest has focused on identifying microbial signals/triggers in the search for effective therapeutic targets. We describe the establishment of the Australian IBD Microbiota (AIM) Study, Australia's first longitudinal IBD bioresource, which will identify and correlate longitudinal microbial and metagenomics signals to disease activity as evaluated by validated clinical instruments, patient-reported surveys, as well as biomarkers. The AIM Study will also gather extensive demographic, clinical, lifestyle and dietary data known to influence microbial composition in order to generate a more complete understanding of the interplay between patients with IBD and their microbiota., Methods: The AIM Study is an Australian multicentre longitudinal prospective cohort study, which will enrol 1000 participants; 500 patients with IBD and 500 healthy controls over a 5-year period. Assessment occurs at 3 monthly intervals over a 24-month period. At each assessment oral and faecal samples are self-collected along with patient-reported outcome measures, with clinical data also collected at baseline, 12 and 24 months. Intestinal tissue will be sampled whenever a colonoscopy is performed. Dietary intake, general health and psychological state will be assessed using validated self-report questionnaires. Samples will undergo metagenomic, transcriptomic, proteomic, metabolomic and culturomic analyses. Omics data will be integrated with clinical data to identify predictive biomarkers of response to therapy, disease behaviour and environmental factors in patients with IBD., Ethics and Dissemination: Ethical approval for this study has been obtained from the South Eastern Sydney Local Health District Research Ethics Committee (HREC 2019/ETH11443). Findings will be reported at national and international gastroenterology meetings and published in peer-reviewed journals., Trial Registration Number: ACTRN12619000911190., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Prostate cancer (CaP) is the most common cancer in men and the second leading cause of cancer deaths in males in Australia. Although serum prostate-specific antigen (PSA) has been the most widely used biomarker in CaP detection for decades, PSA screening has limitations such as low specificity and potential association with over-diagnosis. Current biomarkers used in the clinic are not useful for the early detection of CaP, or monitoring its progression, and have limited value in predicting response to treatment. Urine is an ideal body fluid for the detection of protein markers of CaP and is emerging as a potential source for biomarker discovery. Gene-based biomarkers in urine such as prostate cancer antigen-3 (PCA3), and genes for transmembrane protease serine-2 (TMPRSS2), and glutathione S-transferase P (GSTP1) have been developed and evaluated in the past decades. Among these biomarkers, urinary PCA3 is the only one approved by the FDA in the USA for clinical use. The study of urine microRNAs (miRNAs) is another burgeoning area for investigating biomarkers to achieve a pre-biopsy prediction of CaP to contribute to early detection. The development of mass spectrometry (MS)-based proteomic techniques has sparked new searches for novel protein markers for many diseases including CaP. Urinary biomarkers for CaP represent a promising alternative or an addition to traditional biomarkers. Future success in biomarker discovery will rely on collaboration between clinics and laboratories. In addition, research efforts need to be moved from biomarker discovery to validation in a large cohort or separate population of patients and translation of these findings to clinical practice. In this review, we discuss urine as a potential source for CaP biomarker discovery, summarise important genetic urine biomarkers in CaP and focus on MS-based proteomic approaches as well as other recent developments in quantitative techniques for CaP urine biomarker discovery., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Neuronal loss in numerous neurodegenerative disorders has been linked to protein aggregation and oxidative stress. Emerging data regarding overlapping proteinopathy in traditionally distinct neurodegenerative diseases suggest that disease-modifying treatments targeting these pathological features may exhibit efficacy across multiple disorders. Here, we describe proteinopathy distinct from classic synucleinopathy, predominantly comprised of the anti-oxidant enzyme superoxide dismutase-1 (SOD1), in the Parkinson's disease brain. Significant expression of this pathology closely reflected the regional pattern of neuronal loss. The protein composition and non-amyloid macrostructure of these novel aggregates closely resembles that of neurotoxic SOD1 deposits in SOD1-associated familial amyotrophic lateral sclerosis (fALS). Consistent with the hypothesis that deposition of protein aggregates in neurodegenerative disorders reflects upstream dysfunction, we demonstrated that SOD1 in the Parkinson's disease brain exhibits evidence of misfolding and metal deficiency, similar to that seen in mutant SOD1 in fALS. Our data suggest common mechanisms of toxic SOD1 aggregation in both disorders and a potential role for SOD1 dysfunction in neuronal loss in the Parkinson's disease brain. This shared restricted proteinopathy highlights the potential translation of therapeutic approaches targeting SOD1 toxicity, already in clinical trials for ALS, into disease-modifying treatments for Parkinson's disease.

Radioresistance is a major challenge for prostate cancer (CaP) metastasis and recurrence after radiotherapy. This study aimed to identify potential protein markers and signaling pathways associated with radioresistance using a PC-3 radioresistant (RR) subcutaneous xenograft mouse model and verify the radiosensitization effect from a selected potential candidate. PC-3RR and PC-3 xenograft tumors were established and differential protein expression profiles from two groups of xenografts were analyzed using liquid chromatography tandem-mass spectrometry. One selected glycolysis marker, lactate dehydrogenase A (LDHA) was validated, and further investigated for its role in CaP radioresistance. We found that 378 proteins and 51 pathways were significantly differentially expressed between PC-3RR and PC-3 xenograft tumors, and that the glycolysis pathway is closely linked with CaP radioresistance. In addition, we also demonstrated that knock down of LDHA with siRNA or inhibition of LDHA activity with a LDHA specific inhibitor (FX-11), could sensitize PC-3RR cells to radiotherapy with reduced epithelial-mesenchymal transition, hypoxia, DNA repair ability and autophagy, as well as increased DNA double strand breaks and apoptosis. In summary, we identified a list of potential RR protein markers and important signaling pathways from a PC-3RR xenograft mouse model, and demonstrate that targeting LDHA combined with radiotherapy could increase radiosensitivity in RR CaP cells, suggesting that LDHA is an ideal therapeutic target to develop combination therapy for overcoming CaP radioresistance.

Introduction: Chemoresistance is a major challenge to current ovarian cancer chemotherapy. It is important to identify biomarkers to distinguish chemosensitive and chemoresistant patients. Areas covered: We review the medical literature, discuss MS-based technologies with respect to chemoresistant ovarian cancer and summarize the promising chemoresistant biomarkers identified. In addition, the challenges and future perspectives of biomarker discovery research are explored. With the employment of mass spectrometry-based (MS-based) proteomics, biomarker discovery of ovarian cancer has made great progress in the last decade. Many potential biomarkers were identified by MS-based proteomics technologies, some of which have been validated for further extensive studies in clinical settings. Expert commentary: The discovery of chemoresistant biomarkers is a newly developing area and may provide a clue for predicting chemotherapeutic response and discover therapeutic targets for paving the way of personalized medicine. Multiple complementary MS-based proteomics approaches hold promise for finding novel therapeutic targets in ovarian cancer treatment.

Despite early screening programs and new therapeutic strategies, metastatic breast cancer is still the leading cause of cancer death in women in industrialized countries and regions. There is a need for novel biomarkers of susceptibility, progression, and therapeutic response. Global analyses or systems science approaches with omics technologies offer concrete ways forward in biomarker discovery for breast cancer. Previous studies have shown that expression of profilin-1 (PFN1), a ubiquitously expressed actin-binding protein, is downregulated in invasive and metastatic breast cancer. It has also been reported that PFN1 overexpression can suppress tumorigenic ability and motility/invasiveness of breast cancer cells. To obtain insights into the underlying molecular mechanisms of how elevating PFN1 level induces these phenotypic changes in breast cancer cells, we investigated the alteration in global protein expression profiles of breast cancer cells upon stable overexpression of PFN1 by a combination of three different proteome analysis methods (2-DE, iTRAQ, label-free). Using MDA-MB-231 as a model breast cancer cell line, we provide evidence that PFN1 overexpression is associated with alterations in the expression of proteins that have been functionally linked to cell proliferation (FKPB1A, HDGF, MIF, PRDX1, TXNRD1, LGALS1, STMN1, LASP1, S100A11, S100A6), survival (HSPE1, HSPB1, HSPD1, HSPA5 and PPIA, YWHAZ, CFL1, NME1) and motility (CFL1, CORO1B, PFN2, PLS3, FLNA, FLNB, NME2, ARHGDIB). In view of the pleotropic effects of PFN1 overexpression in breast cancer cells as suggested by these new findings, we propose that PFN1-induced phenotypic changes in cancer cells involve multiple mechanisms. Our data reported here might also offer innovative strategies for identification and validation of novel therapeutic targets and companion diagnostics for persons with, or susceptibility to, breast cancer.

The leukocyte immunoglobulin-like receptor (LILR) A3 is a member of the highly homologous activating and inhibitory receptors expressed on leukocytes. LILRA3 is a soluble receptor of unknown functions but is predicted to act as a broad antagonist to other membrane-bound LILRs. Functions of LILRA3 are unclear primarily because of the lack of high quality functional recombinant protein and insufficient knowledge regarding its ligand(s). Here, we expressed and characterized recombinant LILRA3 (rLILRA3) proteins produced in 293T cells, Escherichia coli, and Pichia pastoris. We found that the purified rLILRA3 produced in the mammalian system was the same size as a 70-kDa native macrophage LILRA3. This is 20 kDa larger than the calculated size, suggesting significant post-translational modifications. In contrast, rLILRA3 produced in E. coli was similar in size to the unprocessed protein, but yeast-produced protein was 2-4 times larger than the unprocessed protein. Treatment with peptide-N-glycosidase F reduced the size of the mammalian cell- and yeast-produced rLILRA3 to 50 kDa, suggesting that most modifications are due to glycosylation. Consistent with this, mass spectrometric analysis of the mammalian rLILRA3 revealed canonical N-glycosylation at the predicted Asn(140), Asn(281), Asn(302), Asn(341), and Asn(431) sites. Functionally, only mammalian cell-expressed rLILRA3 bound onto the surface of monocytes with high affinity, and importantly, only this significantly abrogated LPS-induced TNFα production by monocytes. Binding to monocytes was partially blocked by β-lactose, indicating that optimally glycosylated LILRA3 might be critical for ligand binding and function. Overall, our data demonstrated for the first time that LILRA3 is a potential new anti-inflammatory protein, and optimal glycosylation is required for its functions.

The tear film covers and protects the ocular surface. It contains various molecules including a large variety of proteins. The protein composition of the tear fluid can change with respect to various local and systemic diseases. Prior to the advent of the proteomic era, tear protein analysis was limited to a few analytical techniques, the most common of which was immunoelectrophoresis, an approach dependent on antibody availability. Using proteomics, hundreds of tear proteins could potentially be identified and subsequently studied. Although detection of low-abundance proteins in the complex tear proteome remains a challenge, advances in sample fractionation and mass spectrometry have greatly enhanced our ability to detect these proteins. With increasing proteomic applications, tears show great potential as biomarkers in the development of clinical assays for various human diseases. In this chapter, we discuss the structure and functions of the tear film and methods for its collection. We also summarize potential tear protein biomarkers identified using proteomic techniques for both ocular and systemic diseases. Finally, modern proteomic techniques for tear biomarker research and future challenges are explored.

This is the first 2-DE study using sequential dyes to analyse phospho-, glyco- and total tear protein profiles (Pro-Q Diamond for phosphoprotein, Pro-Q Emerald for glycoprotein and Sypro Ruby for total protein). This method minimised the gel-gel variations, allowing better comparisons among the three profiles and generated a whole map of PTM profiles of tear protein. A novel tear protein, dermcidin, was identified for the first time in this study. The identification of this antimicrobial protein suggests a new model of defence in tears. In addition, we are able to present the first experimental evidence of the presence of glycosylated lipocalin 1 and cystatin S. Nucleobindin 2 was only detected using phospho staining, suggesting it is only phosphorylated in tears. This study provides the groundwork for understanding the PTM of tear proteins and consequently these methods could be useful in the search for biomarkers in tears.

The success of proteomics relies heavily in the ability to characterize very diverse species of proteins. This diversity stems from a proteins physicochemical properties, its copy number and abundance and its association with other proteins. Prefractionation and simplification of biological samples prior to downstream MS analysis is showing some virtue in obtaining greater depth of protein analysis. The MicroFlow MF10 is a prefractionation device for low volume, low abundance complex samples that can also enrich for very specific species of proteins based on charge and/or size either in native or denaturing format. It has also been used to desalt and deplete samples of contaminating ions or proteins. Although this instrument is only in its infancy in terms of exploring its capabilities, the technology has been used successfully for the fractionation of plasma proteins Wasinger(1), Omenn GS(2), as well as purification of human growth hormone Catzel D(3) antibodies Cheung(4) and IgY Gee(5) and other complex samples.

Rifaximin resistance in the probiotic strain Bifidobacterium infantis BI07 was studied to assess the use of an antibiotic-probiotic combination for clinical management of intestinal disorders. A rifaximin-resistant mutant was selected and a 129 bp core region of the rpoB gene was sequenced and compared with the respective sequence of the sensitive clone. A miss-sense mutation of codon 513, producing the substitution of Gln with Arg in the protein sequence, was found. The involvement of metabolic changes associated with rifaximin resistance was also investigated by proteomic analysis performed with two-dimensional electrophoresis and mass spectrometry. The principal categories of proteins, whose expression levels varied as a consequence of rifaximin resistance, included chaperonins, regulatory factors and metabolic enzymes. The hypothesis of rifaximin inactivation by bacterial enzymatic activities was excluded, as neither structural modifications nor degradation derivates of the drug moiety was identified using liquid chromatography coupled with tandem mass spectrometry.

Insulin stimulates the translocation of the glucose transporter GLUT4 from intracellular vesicles to the plasma membrane. In the present study we have conducted a comprehensive proteomic analysis of affinity-purified GLUT4 vesicles from 3T3-L1 adipocytes to discover potential regulators of GLUT4 trafficking. In addition to previously identified components of GLUT4 storage vesicles including the insulin-regulated aminopeptidase insulin-regulated aminopeptidase and the vesicle soluble N-ethylmaleimide factor attachment protein (v-SNARE) VAMP2, we have identified three new Rab proteins, Rab10, Rab11, and Rab14, on GLUT4 vesicles. We have also found that the putative Rab GTPase-activating protein AS160 (Akt substrate of 160 kDa) is associated with GLUT4 vesicles in the basal state and dissociates in response to insulin. This association is likely to be mediated by the cytosolic tail of insulin-regulated aminopeptidase, which interacted both in vitro and in vivo with AS160. Consistent with an inhibitory role of AS160 in the basal state, reduced expression of AS160 in adipocytes using short hairpin RNA increased plasma membrane levels of GLUT4 in an insulin-independent manner. These findings support an important role for AS160 in the insulin regulated trafficking of GLUT4.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

Bifidobacteria are Gram-positive prokaryotes that naturally colonize the human gut where they exert several health-promoting effects. The present paper reports the use of a strong cation exchange-reversed-phase-tandem mass spectrometry strategy to catalogue the most abundantly expressed proteins of a probiotic Bifidobacterium infantis strain. A global view of the B. infantis proteome was obtained. The bimodal representation of the proteins identified by mass spectrometry provides the first theoretical two-dimensional map of protein distribution for this organism. Among the 136 proteins identified by multidimensional protein identification technology (MudPIT) analysis, 118 showed the highest similarity with the translated sequences of B. longum genome, two proteins were similar to other Bifidobacterium species and the remaining 16 were similar to different genera. Specific biological activities have been assigned to 115 identified proteins, whereas 21 have been referred to the group of hypothetical proteins. The MudPIT approach allowed us to identify high mass and basic isoelectric point proteins that are generally challenging to visualize using the traditional two-dimensional electrophoresis technique. Redundancy in peptide and protein identification using the double chromatography technique was also evaluated.

Sphingopyxis (formerly Sphingomonas) alaskensis is a model bacterium for studying adaptation to oligotrophy (nutrient-limitation). It has a unique physiology which is fundamentally different to that of the well studied bacteria such as Escherichia coli. To begin to identify the genes involved in its physiological responses to nutrient-limited growth and starvation, we developed high resolution two-dimensional electrophoresis (2-DE) methods and determined the identity of 12 proteins from a total of 21 spots using mass spectrometric approaches and cross-species matching. The best matches were to Novosphingobium aromaticivorans; a terrestrial, hydrocarbon degrading bacterium which was previously classified in the genus Sphingomonas. The proteins identified are involved in fundamental cellular processes including protein synthesis, protein folding, energy generation and electron transport. We also compared radiolabelled and silver-stained 2-DE gels generated with the same protein samples and found significant differences in the protein profiles. The use of both methods increased the total number of proteins with differential spot intensities which could be identified from a single protein sample. The ability to effectively utilise cross-species matching from radiolabelled and silver-stained gels provides new approaches for determining the genetic basis of microbial oligotrophy.

Small cell lung cancer (SCLC) initially responds well to chemotherapy and fractionated radiotherapy, but resistance to these treatments eventually develops in the vast majority of cases. To understand how resistance develops in the H69 SCLC cell line, we compared the changes in gene expression associated with 37.5 Gy fractionated X-ray treatment that produced the stable radiation- and drug-resistant H69/R38 cell subline to the changes associated with a single 4- or 8-Gy X-ray treatment. Gene expression was determined by suppression subtractive hybridization combined with Northern blot analysis and two-dimensional (2D) protein electrophoresis. Stable radiation and drug resistance was associated with coordinate changes in the expression of genes of the cytoskeleton, protein synthesis, cell cycle, redox/stress and metabolic pathways. The pattern of these changes was remarkably similar to the changes seen 24 h after a single X-ray treatment of the H69 cells but differed from the changes in expression associated with a single X-ray treatment of the resistant H69/ R38 cells. Stable radiation and drug resistance may be caused by the constitutive expression of those genes transiently expressed by sensitive cells in response to a single X-ray dose. The repeated treatments received during fractionated irradiation may promote the change from a transient to a constitutive pattern of gene expression.

Growth factor regulation of the cortical actin cytoskeleton is fundamental to a wide variety of cellular processes. The cortical actin-associated protein, cortactin, regulates the formation of dynamic actin networks via the actin-related protein (Arp)2/3 complex and hence is a key mediator of such responses. In order to reveal novel roles for this versatile protein, we used a proteomics-based approach to isolate cortactin-interacting proteins. This identified several proteins, including CD2-associated protein (CD2AP), as targets for the cortactin Src homology 3 domain. Co-immunoprecipitation of CD2AP with cortactin occurred at endogenous expression levels, was transiently induced by epidermal growth factor (EGF) treatment, and required the cortactin Src homology 3 domain. The CD2AP-binding site for cortactin mapped to the second of three proline-rich regions. Because CD2AP is closely related to Cbl-interacting protein of 85 kDa (CIN85), which regulates growth factor receptor down-regulation via complex formation with Cbl and endophilin, we investigated whether the CD2AP-cortactin complex performs a similar function. EGF treatment of cells led to transient association of Cbl and the epidermal growth factor receptor (EGFR) with a constitutive CD2AP-endophilin complex. Cortactin was recruited into this complex with slightly delayed kinetics compared with Cbl and the EGFR. Immunofluorescence analysis revealed that the EGFR, CD2AP, and cortactin co-localized in regions of EGF-induced membrane ruffles. Therefore, by binding both CD2AP and the Arp2/3 complex, cortactin links receptor endocytosis to actin polymerization, which may facilitate the trafficking of internalized growth factor receptors.

Analysis of complex protein samples by two-dimensional electrophoresis (2-DE) is often more difficult in the presence of a few predominant proteins. In plasma, proteins such as albumin mask proteins of lower abundance, as well as significantly limiting the amount of protein that can be loaded onto the immobilized pH gradient strip. In this paper the Gradiflow, a preparative electrophoresis system, has been used to deplete human plasma of the highly abundant protein albumin under native and denatured conditions. A three step protocol incorporating a charge separation to collect proteins with an isoelectric point greater than albumin and two size separations to isolate proteins larger and smaller than albumin, was used. When the albumin depleted fractions were analysed on pH 3-10 2-DE gels, proteins that were masked by albumin were revealed and proteins not seen in the unfractionated plasma sample were visualised. Matrix-assisted laser desorption/ionisation-time of flight mass spectrometry analysis confirmed the identification of the protein that lies beneath albumin to be C4B-binding protein alpha chain. The liquid fractions from the Gradiflow separations were also analysed by liquid chromatography-tandem mass spectrometry to confirm the proteins were separated according to their size and charge mobility in an electric field.

Proteomic research, for its part, is benefiting enormously from the last decade of genomic research as we now have archived, annotated and audited sequence databases to correlate and query experimental data. While the two-dimensional electrophoresis (2-DE) gels are still a central part of proteomics, we reflect on the possibilities and realities of the current 2-DE technology with regard to displaying and analysing proteomes. Limitations of analysing whole cell/tissue lysates by 2-DE alone are discussed, and we investigate whether extremely narrow p/ranges (1 pH unit/25 cm) provide a solution to display comprehensive protein expression profiles. We are confronted with a challenging task: the dynamic range of protein expression. We believe that most of the existing technology is capable of displaying many more proteins than is currently achievable by integrating existing and new techniques to prefractionate samples prior to 2-DE display or analysis. The availability of a "proteomics toolbox", consisting of defined reagents, methods, and equipment, would assist a comprehensive analysis of defined biological systems.

Mycoplasma genitalium is the smallest member of the class Mollicutes, with a genome size of 580 kb. It has the potential to express 480 gene products, and is therefore considered to be an excellent model to assess: (a) the minimum metabolism required by a free living cell; and (b) proteomic technologies and the information obtained by proteome analysis. Here, we report on the most complete proteome observed at 73% (expected proteome), and analysed at 33% (reported proteome). The use of four overlapping pH windows in conjunction with SDS/PAGE has allowed 427 distinct proteins to be resolved in association with the exponential growth of M. genitalium. Proof of expression for 201 proteins of sufficient abundance on silver stained two-dimensional gels was obtained using peptide mass fingerprinting (PMF) of which 158 were identified. The potential for gene product modification in even the simplest known self-replicating organism was quantified at a ratio of 1.22 : 1, more proteins than genes. A reduction in protein expression of 42% was observed for post-exponentially-grown cells. DnaK, GroEL, DNA gyrase, and a cytadherence accessory protein were significantly elevated, while some ribosomal proteins were reduced in relative abundance. The strengths and weaknesses of techniques employed were assessed with respect to the observed and predicted proteome derived from DNA sequence information. Proteomics was shown to provide a perspective into the biochemical and metabolic activities of this organism, beyond that obtainable by sequencing alone.

The identity of 45 protein spots representing 32 orthologues within the Ochrobactrum anthropi proteome within a gradient of pH 4-7, and mass range 5-90 kDa were determined across species boundaries. These proteins could be classified into 13 functional categories and establish metabolic, regulatory and translatory systems including amino acid biosynthesis, electron transport and the potential for plant symbiosis in a molecularly understudied organism. Amino acid composition and/or peptide mass fingerprinting were employed as a means to search the Swiss-Prot and OWL protein sequence databases for similarity within a broad taxonomic class of bacteria. Candidate matches from database searches could be compared and a simple multiplication matrix based on co-occurrence and rank within the top 96 most similar entries was used to provide statistical confidence. This mathematical matrix was evaluated with respect to the characterisation of O. anthropi, an unsequenced and understudied bacterium, in the light of the recent influx of DNA sequence information.