Proteomics Analysis of A33 Immunoaffinity-purified Exosomes Released from the Human Colon Tumor Cell Line LIM1215 Reveals a Tissue-specific Protein Signature

Exosomes are 40–100-nm-diameter nanovesicles of endocytic origin that are released from diverse cell types. To better understand the biological role of exosomes and to avoid confounding data arising from proteinaceous contaminants, it is important to work with highly purified material. Here, we describe an immunoaffinity capture method using the colon epithelial cell-specific A33 antibody to purify colorectal cancer cell (LIM1215)-derived exosomes. LC-MS/MS revealed 394 unique exosomal proteins of which 112 proteins (28%) contained signal peptides and a significant enrichment of proteins containing coiled coil, RAS, and MIRO domains. A comparative protein profiling analysis of LIM1215-, murine mast cell-, and human urine-derived exosomes revealed a subset of proteins common to all exosomes such as endosomal sorting complex required for transport (ESCRT) proteins, tetraspanins, signaling, trafficking, and cytoskeletal proteins. A conspicuous finding of this comparative analysis was the presence of host cell-specific (LIM1215 exosome) proteins such as A33, cadherin-17, carcinoembryonic antigen, epithelial cell surface antigen (EpCAM), proliferating cell nuclear antigen, epidermal growth factor receptor, mucin 13, misshapen-like kinase 1, keratin 18, mitogen-activated protein kinase 4, claudins (1, 3, and 7), centrosomal protein 55 kDa, and ephrin-B1 and -B2. Furthermore, we report the presence of the enzyme phospholipid scramblase implicated in transbilayer lipid distribution membrane remodeling. The LIM1215-specific exosomal proteins identified in this study may provide insights into colon cancer biology and potential diagnostic biomarkers.Exosomes represent a distinct class of membrane nanovesicles (40–100-nm diameter) of endocytic origin that are released from diverse cell types under both normal and pathological conditions (1). Although initial studies focused on exosomes released from various cell types in vitro, exosomes have also been reported in diverse body fluids such as urine (2), amniotic fluid (3, 4), malignant ascites (5–7), bronchoalveolar lavage fluid (8), synovial fluid (9), platelets (10), breast milk (11), and blood (12). Exosomes are formed through the inward budding of late endosomal membranes that give rise to intraluminal vesicles (ILVs)1 within intracellular multivesicular bodies (MVBs). MVBs have a well known intermediary function in the degradation of either proteins internalized from the cell surface (e.g. cell surface receptors) or intracellular proteins sorted from the trans-Golgi network. Proteins destined for degradation are sorted, typically in a ubiquitin-dependent manner, into the ILVs of the nascent MVBs, which then fuse with pre-existing lysosomes (13). An alternate fate for MVBs involves their fusion with the plasma membrane and ensuing release of ILVs into the extracellular environment as exosomes. The biogenesis of exosomes has been linked to the protein complex ESCRT machinery, which is required for both formation of MVBs and the recruitment of their endosome-derived cargo proteins (14).Exosomes exhibit pleiotropic biological functions including immunomodulatory activity, mediation of cell-cell communication, and, possibly, the transport and propagation of infectious cargo such as prions and retroviruses (1, 15, 16). Despite these advances in our understanding of exosome function, the physiological significance of exosomes is still not fully understood. The observation that exosomes contains inactive RNA and microRNAs that can be transferred to another cell and be translated in the recipient suggest that exosomes may provide a novel vehicle for genetic exchange between cells (17). More recently, the finding of glioblastoma tumor cell-derived exosomes that contain mRNA mutant/variants and microRNAs characteristic of the glioma coupled with the finding of these microvesicles in serum of glioblastoma patients suggests that blood-based exosomes may provide important diagnostic information and aid in therapeutic decisions for cancer patients (18).The molecular composition of exosomes purified from the cell culture medium from various cell types and diverse body fluids has been analyzed by proteomics as well as fluorescence-activated cell sorting, Western blot analysis, and immunohistochemistry (1, 19). In addition to displaying a protein composition that reflects their endosomal origin, these proteome profiling studies also indicate a unique protein fingerprint that reflects their cellular origin as well as possible physiological role and targeting properties. However, interpretation of exosomal proteome profiles in a biological context also highlights a cautionary note, especially if exosomes are not highly purified. For example, retroviruses such as HIV particles that bud from the cell surface using the same endocytic pathway machinery as exosomes to egress from hematopoietic cells can be a confounding factor in biochemical and physiological analyses of exosomes. Furthermore, exosomes and HIV-1 particles have similar biophysical properties such as size (40–100 and 100 nm, respectively) and buoyant density (1.13–1.21 g/liter (20) and 1.13–1.21 g/liter (21), respectively) as well as molecular composition and their ability to activate immune cells. Although earlier studies describe exosomes carrying virion cargo (22–24), recent exosome purification strategies deploying immunoaffinity capture (25) or a combination of immunoaffinity capture and density gradient centrifugation (26) demonstrate that exosomes from hematopoietic cells can be purified free of virions like HIV-1.In-depth proteomics studies with large data sets that might contribute to the understanding of the biological function of exosomes are, to date, limited (2, 17). Moreover, strategies used to purify exosomes differ between laboratories (1) with little consensus concerning criteria of purity. Isolation strategies typically involve a combination of differential centrifugation, filtration, concentration, and flotation density gradient followed by characterization using electron microscopy, flow cytometry, and Western blotting (for a review, see Simpson et al. (1)). As a first step toward understanding the physiological role of exosomes in colon cancer biology, we describe here a robust strategy to isolate and characterize exosomes released from LIM1215 colorectal carcinoma cells (27) for the purpose of proteome analysis. This isolation strategy utilized the colon epithelial cell-specific A33 antibody (28–31) to immunoaffinity capture A33-containing exosomes using microbeads. Here, we report for the first time an in-depth proteomics analysis of A33-containing exosomes released from the LIM1215 colon carcinoma cell line. Using these data, we performed a comparative bioinformatics analysis with human urinary and mast cell-derived exosomes.     

Activation of an Olfactory Receptor Inhibits Proliferation of Prostate Cancer Cells

Olfactory receptors (ORs) are expressed not only in the sensory neurons of the olfactory epithelium, where they detect volatile substances, but also in various other tissues where their potential functions are largely unknown. Here, we report the physiological characterization of human OR51E2, also named prostate-specific G-protein-coupled receptor (PSGR) due to its reported up-regulation in prostate cancer. We identified androstenone derivatives as ligands for the recombinant receptor. PSGR can also be activated with the odorant β-ionone. Activation of the endogenous receptor in prostate cancer cells by the identified ligands evoked an intracellular Ca²⁺ increase. Exposure to β-ionone resulted in the activation of members of the MAPK family and inhibition of cell proliferation. Our data give support to the hypothesis that because PSGR signaling could reduce growth of prostate cancer cells, specific receptor ligands might therefore be potential candidates for prostate cancer treatment.Excessive signaling by G-protein-coupled receptors (GPCRs)³ such as endothelin A receptor (1), bradykinin 1 receptor (2), follicle-stimulating hormone receptor (3), and thrombin receptor (4, 5) is known to occur in prostate cancers due to strong overexpression of the respective receptors. Activation of some of these GPCRs results in androgen-independent androgen receptor activation, thus promoting the transition of prostate cancer cells from an androgen-dependent to an androgen-independent state (6, 7).The prostate-specific G-protein-coupled receptor (PSGR) is a class A GPCR that was initially identified as a prostate-specific tumor biomarker (8–10). It is specifically expressed in prostate epithelial cells, and its expression increases significantly in human prostate intraepithelial neoplasia and prostate tumors, suggesting that PSGR may play an important role in early prostate cancer development and progression (9, 11). Although expression of the human PSGR was found to be prostate-specific (10, 12), mRNA can also be detected in the olfactory zone and the medulla oblongata of the human brain (12). Human PSGR shares 93% amino acid homology to the respective mouse and rat homologues, which are also expressed in the brain (12). Interestingly, PSGR has numerous sequence motifs in common with the large superfamily of olfactory receptors (ORs), which build the largest class of human GPCRs and allow the recognition of a wide range of structurally diverse molecules in the nasal epithelium (13–15). Recently, also the steroid hormones androstenone and androstadienone were identified as OR ligands (16). In addition to their role in the sensory neurons of the nose, ORs have been found in different tissues throughout the body (17, 18). Their function(s) in these extranasal locations are questionable except for in a few cases where functional studies have been performed in spermatozoa (19, 20) and in enterochromaffin cells of the gastrointestinal tract (21).Here, we report the identification of steroid ligands of heterologously expressed PSGR and investigate the functional relevance of PSGR expression in prostate tissue. Steroid hormones elicited rapid Ca²⁺ responses in the LNCaP prostate cancer cell line and in primary human prostate epithelial cells. Moreover, activated PSGR causes phosphorylation of p38 and stress-activated protein kinase/c-Jun NH₂-terminal kinase (SAPK/JNK) mitogen-activated protein kinases (MAPKs), resulting in reduced proliferation rates in prostate cancer cells.     

Proteomics Analysis of Bladder Cancer Exosomes

Exosomes are nanometer-sized vesicles, secreted by various cell types, present in biological fluids that are particularly rich in membrane proteins. Ex vivo analysis of exosomes may provide biomarker discovery platforms and form non-invasive tools for disease diagnosis and monitoring. These vesicles have never before been studied in the context of bladder cancer, a major malignancy of the urological tract. We present the first proteomics analysis of bladder cancer cell exosomes. Using ultracentrifugation on a sucrose cushion, exosomes were highly purified from cultured HT1376 bladder cancer cells and verified as low in contaminants by Western blotting and flow cytometry of exosome-coated beads. Solubilization in a buffer containing SDS and DTT was essential for achieving proteomics analysis using an LC-MALDI-TOF/TOF MS approach. We report 353 high quality identifications with 72 proteins not previously identified by other human exosome proteomics studies. Overrepresentation analysis to compare this data set with previous exosome proteomics studies (using the ExoCarta database) revealed that the proteome was consistent with that of various exosomes with particular overlap with exosomes of carcinoma origin. Interrogating the Gene Ontology database highlighted a strong association of this proteome with carcinoma of bladder and other sites. The data also highlighted how homology among human leukocyte antigen haplotypes may confound MASCOT designation of major histocompatability complex Class I nomenclature, requiring data from PCR-based human leukocyte antigen haplotyping to clarify anomalous identifications. Validation of 18 MS protein identifications (including basigin, galectin-3, trophoblast glycoprotein (5T4), and others) was performed by a combination of Western blotting, flotation on linear sucrose gradients, and flow cytometry, confirming their exosomal expression. Some were confirmed positive on urinary exosomes from a bladder cancer patient. In summary, the exosome proteomics data set presented is of unrivaled quality. The data will aid in the development of urine exosome-based clinical tools for monitoring disease and will inform follow-up studies into varied aspects of exosome manufacture and function.Bladder cancer is one of the eight most frequent cancers in the Western world, and the frequency of transitional cell carcinoma (TCC),¹ which accounts for 90% of bladder cancers, is second only to prostate cancer as a malignancy of the genitourinary tract. Urine cytology and cystoscopy remain the predominant clinical tools for diagnosing and monitoring the disease, but cytology is poorly sensitive, particularly for low grade tumors, and does not serve as a prognostic tool. Cystoscopy is an invasive procedure, and there is pressing need to identify informative molecular markers that can be used to replace it.Recently, small cell-derived vesicles termed exosomes that are present in body fluids (1–5) have been proposed as a potential source of diagnostic markers (2, 6–8). These nanometer-sized vesicles, which are secreted by most cell types, originate from multivesicular bodies of the endocytic tract and reflect a subproteome of the cell. Exosomes are enriched in membrane and cytosolic proteins, and this molecular repertoire appears to be of particular functional importance to the immune system (9). Exosomes also comprise an array of lipids, mRNA, and microRNA, which are likely involved in conveying intercellular communication processes (10). Importantly, many exosomal components are simply not present as free soluble molecules in body fluids, such as certain microRNA species, which are encapsulated within the exosome lumen (6, 10). Therefore, the ability to isolate exosomes from urine (2), plasma (1), saliva (11), or other physiological sources (3) holds significant potential for obtaining novel and complex sets of biomarkers in a non-invasive manner. Exosome analysis may therefore be of value in disease diagnosis and monitoring in a variety of settings (6, 7, 12–14).Exosomes as indicators of pathology were first documented in the context of renal injury where a differential proteomics approach revealed changes in urinary exosome phenotype following renal injury (7). The researchers identified exosomally expressed Fetuin-A as a marker that became elevated 50-fold within hours following nephrotoxin exposure in rodents. Exosomal Fetuin-A elevation was also apparent in patients with acute renal injury before changes in urinary creatinine were observed (7). Clinical exosome analysis may also prove useful for solid cancers, such as ovarian or lung cancer, where the quantity of epithelial cell adhesion molecule-positive serum exosomes may correlate with tumor stage/grade. Such disease-associated exosomes express microRNA species not detected in healthy subjects (6, 12), although in this respect, there is little correlation between microRNA and disease bulk (6, 12). Other recent examples include studies of urinary exosomes in prostate cancer with exosomes expressing protein markers 5T4 (15), prostate cancer gene 3 (PCA-3) (8), or mRNA (TMPRSS2-ERG) (8, 16) associated with prostate cancer. To our knowledge, exosomes have not yet been studied in the context of other urological malignancies such as renal cancer, and to date, only one report describes the urine-derived microparticles from bladder cancer patients (17). In that report, they examined the proteome of a highly complex mixture of microvesicles, exosomes, and other urinary constituents that can be pelleted by high speed ultracentrifugation, identifying eight proteins that may be elevated in cancer. However, given the nature of the sample analyzed, it is unknown whether these proteins are exosomally expressed.Identification of the principal and most relevant molecular markers in these and other clinical scenarios remains a major challenge. In part, this is because exosomes present within complex body fluids originate from heterogeneous cell types. For example, plasma exosomes may be derived from platelets, lymphocytes, or endothelial cells (1), and a proportion may arise from well perfused organs such as the liver (18) and likely other organs as well (16). Similarly, exosomes present in urine arise from urothelial cells of the kidney and downstream of the renal tract (2, 8, 15).Importantly, all proteomics studies of exosomes isolated from body fluids are unavoidably complicated by the presence of high abundance non-exosomal proteins contaminating the preparations. Examples include albumin, immunoglobulin, and complement components present in exosomes prepared from malignant effusions (5) and Tamm-Horsfall protein present in exosomes purified from urine (2). As such, great care must be taken in the interpretation of the large data sets produced by proteomics studies, requiring careful validation of the proteins of interest. The protein composition of exosomes using a single homogenous cell type is one approach that may be used to uncover the protein components of exosomes produced by various cell types.There remain two major issues in the realm of exosome proteomics that complicate our interpretation of lists of identified proteins. Foremost are the diverse methods chosen for exosome purification that in some studies have involved attempts to remove contaminants through a key biophysical property of the vesicles, i.e. their capacity to float on sucrose (19, 20) or other dense media (21). Not all published studies, however, have taken such steps, preferring a far simpler pellet (or pellet and wash) approach. These latter preparations may be significantly contaminated by components of the cellular secretome, cell fragments, and other components. All of these factors could lead to false positive identifications of exosome proteins. The second key issue centers on the MS approaches utilized in various exosome proteomics studies. Many early examples relied only on a peptide mass fingerprinting approach, lacking robust peptide sequence data (22, 23), and more recently, search criteria that are generally recommended for MS-derived sequence data have not been specified in all studies. In this study, we have listed only those proteins identified by good quality MS/MS data for two or more peptides. Variability in the robustness and bias in bioinformatics analysis of data sets and in the steps taken to validate identified proteins is an additional factor that impacts the confidence in the identification lists produced.In this study, we aimed to perform the first proteomics analysis of human bladder cancer exosomes. We took extensive steps to produce high purity and quality-assured exosome preparations prior to beginning proteomics workflows. Solubilizing the sample with SDS and a reducing agent (DTT) was a critical step that allowed for global protein identification using nanoscale liquid chromatography followed by MALDI-TOF/TOF mass spectrometry. In this study, we present the identification of a significant number of exosomally expressed proteins (353 in total) of unrivaled quality. Critical manual examination of these identifications revealed issues with multiple (physiologically impossible) MHC Class I identifications that were attributed to a misdesignation of nomenclature by MASCOT due to peptide (and target protein) homology. The data were subjected to unbiased overrepresentation analysis (examining ExoCarta and Gene Ontology databases) to reveal a proteome consistent with exosomes, particularly of carcinoma origin. Validation of several identified proteins, by combining ultracentrifugation on a linear sucrose gradient with Western blotting and/or analysis of exosome-coated latex beads, demonstrated correct surface orientation of several MS-identified membrane proteins at densities consistent with exosomes.The robust approaches taken emphasize our confidence in the validity of the identifications generated and highlight that 72 (of 353) proteins have not been previously shown to be exosomally expressed by other human proteomics studies. The data will be useful for future studies in this underinvestigated disease and will form a platform not only for future clinical validation of some of these putative markers but also to aid further investigations into novel aspects of exosome function and manufacture.     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Proteomics Analysis of Cancer Exosomes Using a Novel Modified Aptamer-based Array (SOMAscanTM) Platform

We have used a novel affinity-based proteomics technology to examine the protein signature of small secreted extracellular vesicles called exosomes. The technology uses a new class of protein binding reagents called SOMAmers® (slow off-rate modified aptamers) and allows the simultaneous precise measurement of over 1000 proteins. Exosomes were highly purified from the Du145 prostate cancer cell line, by pooling selected fractions from a continuous sucrose gradient (within the density range of 1.1 to 1.2 g/ml), and examined under standard conditions or with additional detergent treatment by the SOMAscan^TM array (version 3.0). Lysates of Du145 cells were also prepared, and the profiles were compared. Housekeeping proteins such as cyclophilin-A, LDH, and Hsp70 were present in exosomes, and we identified almost 100 proteins that were enriched in exosomes relative to cells. These included proteins of known association with cancer exosomes such as MFG-E8, integrins, and MET, and also those less widely reported as exosomally associated, such as ROR1 and ITIH4. Several proteins with no previously known exosomal association were confirmed as exosomally expressed in experiments using individual SOMAmer® reagents or antibodies in micro-plate assays. Western blotting confirmed the SOMAscan^TM-identified enrichment of exosomal NOTCH-3, L1CAM, RAC1, and ADAM9. In conclusion, we describe here over 300 proteins of hitherto unknown association with prostate cancer exosomes and suggest that the SOMAmer®-based assay technology is an effective proteomics platform for exosome-associated biomarker discovery in diverse clinical settings.Prostate carcinoma is the most frequent male cancer, with an estimated 240,000 newly diagnosed individuals and 28,000 deaths in the United States during 2012 (National Cancer Institute (NIH)). Methods for detecting this cancer are based on a combination of physical examination through digital rectal examination, clinical imaging, quantification of circulating levels of prostate specific antigen (PSA),¹ and transrectal ultrasound-guided biopsy. As a non-invasive test, PSA measurement is still widely used, but it remains insensitive, as around 15% of men with normal levels of PSA will have prostate cancer according to biopsy results (1), and 60% of men with elevated PSA levels may have other, noncancerous conditions but be subjected to further, unnecessary investigations and interventions (2). PSA may be of better utility in monitoring disease progression (2). An ability to diagnose the disease more specifically at an early stage is likely to save lives and alleviate the healthcare burden and morbidities arising from misdiagnosis. In addition, methods for monitoring the course of the disease in a non-invasive and perhaps predictive manner would offer increased patient benefit, enabling early detection of imminent relapse under hormone therapy, for example. Therefore there is a clinical need for improved molecular approaches for disease diagnosis and monitoring in these settings.Small vesicles termed exosomes are present in body fluids, including serum, plasma, urine, and seminal plasma (3–7), and their isolation and examiniation may prove useful as a minimally invasive means of obtaining a complex set of disease markers. Exosomes are secreted by most, if not all, cell types and are generally accepted as derived principally from multivesicular bodies of the late endocytic tract (8), although examples of plasma membrane budding nanovesicles of similar phenotype have also been described (9). Exosomes are particularly enriched in membrane proteins and in factors related to such endosomal compartments. They also contain proteins found in the cytosol, but they poorly represent components of organelles such as the mitochondria, nucleus, and endoplasmic reticulum (10). Exosomes also comprise an assortment of coding and noncoding RNA. There has been considerable global effort toward defining disease-related alterations in exosomal RNA. However, it is well established that aberrant alterations in cancer cells in response to metabolic, hypoxic, or other forms of stress are reflected in protein changes in the exosomes produced (11–13). Thus exosomes from diseased origins can be distinguished from those of a normal phenotype based on their protein profiles alone.Proteomics studies using mass spectrometry (MS) have previously been conducted on prostate cancer exosomes/microvesicles obtained from cell lines (14, 15), xenotransplantation models (16), or ex vivo biofluids (17). Hundreds of proteins with putative associations with exosomes/microvesicles have been identified. These studies highlight several interesting candidate markers of potential biomarker utility that are currently being explored. However, global proteomic approaches of this nature can have two major limitations. Although the most abundant proteins are more likely to be identified by MS, it is difficult to infer information about relative abundances of proteins in complex samples when using these methods. Secondly, given the often exacting, difficult-to-reproduce, and time-consuming workflows involved, such technologies are poorly suited for the analysis of a large number of samples. Multiplex protein array methodologies have the potential to overcome such issues and offer quantification and options for more rapid sample throughput. However, most platforms are based on antibodies, and these arrays are typically limited to <100 proteins, principally because the cross-reactivity of secondary antibodies can negatively affect assay specificity (18).A recently developed proteomics platform, termed SOMAscan^TM, provides a new generation of protein detection technologies. The platform is capable of the simultaneous quantitative analysis of 1129 proteins per sample in its current form. It is also an approach well suited to handling large numbers of specimens required for well-powered clinical studies (19). The key to this technology, which is described in detail by Gold et al. (20, 21), is the use of slow off-rate modified aptamers (SOMAmers) containing chemically modified nucleotides. This confers greater stability, expanded target range, and improved affinity for the target proteins. This multiplex platform has been applied successfully to small volumes (∼15 μl) of plasma specimens from chronic renal disease patients (20), serum specimens from mesothelioma (22) or lung cancer patients (19), tissue lysates (23), and cerebrospinal fluid (24). However, to date, the compatibility of this array technology with exosomes as the specimen has not been investigated.The purpose of the current study was to examine the utility of this evolving technology in profiling the protein repertoire of exosomes. Research was conducted using highly pure exosomes isolated from a prostate cancer cell line, and we compared this sample to the protein profile of the parent cells. By so doing, we obtained evidence of the compatibility of the platform with this difficult, membranous sample and identified several proteins of previously unknown association with exosomes. In summary, SOMAscan^TM is a versatile tool for probing the composition of exosomes and is a suitable platform to provide a high-throughput approach for exosome-based biomarker discovery in prostate cancer and other clinical settings.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]