Raman and infra-red microspectroscopy: towards quantitative evaluation for clinical research by ratiometric analysis

Biomolecular structure elucidation is one of the major techniques for studying the basic processes of life. These processes get modulated, hindered or altered due to various causes like diseases, which is why biomolecular analysis and imaging play an important role in diagnosis, treatment prognosis and monitoring. Vibrational spectroscopy (IR and Raman), which is a molecular bond specific technique, can assist the researcher in chemical structure interpretation. Based on the combination with microscopy, vibrational microspectroscopy is currently emerging as an important tool for biomedical research, with a spatial resolution at the cellular and sub-cellular level. These techniques offer various advantages, enabling label-free, biomolecular fingerprinting in the native state. However, the complexity involved in deciphering the required information from a spectrum hampered their entry into the clinic. Today with the advent of automated algorithms, vibrational microspectroscopy excels in the field of spectropathology. However, researchers should be aware of how quantification based on absolute band intensities may be affected by instrumental parameters, sample thickness, water content, substrate backgrounds and other possible artefacts. In this review these practical issues and their effects on the quantification of biomolecules will be discussed in detail. In many cases ratiometric analysis can help to circumvent these problems and enable the quantitative study of biological samples, including ratiometric imaging in 1D, 2D and 3D. We provide an extensive overview from the recent scientific literature on IR and Raman band ratios used for studying biological systems and for disease diagnosis and treatment prognosis.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

A glimpse into the clinical proteome of human malaria parasites Plasmodium falciparum and Plasmodium vivax

Malaria causes a worldwide annual mortality of about a million people.Rapidly evolving drug-resistant species of the parasite have created a pressing need for the identification of new drug targets and vaccine candidates. By developing fractionation protocols to enrich parasites from low-parasitemia patient samples, we have carried out the first ever proteomics analysis of clinical isolates of early stages of Plasmodium falciparum (Pf) and P. vivax. Patient-derived malarial parasites were directly processed and analyzed using shotgun proteomics approach using high-sensitivity MS for protein identification. Our study revealed about 100 parasite-coded gene products that included many known drug targets such as Pf hypoxanthine guanine phosphoribosyl transferase, Pf L-lactate dehydrogenase, and Plasmepsins. In addition,our study reports the expression of several parasite proteins in clinical ring stages that have never been reported in the ring stages of the laboratory-cultivated parasite strain. This proof-of-principle study represents a noteworthy step forward in our understanding of pathways elaborated by the parasite within the malaria patient and will pave the way towards identification of new drug and vaccine targets that can aid malaria therapy.

Identification of genes associated with tumorigenesis of meibomian cell carcinoma by microarray analysis

Meibomian cell carcinoma (MCC) is a malignant tumor of the meibomian glands located in the eyelids. No information exists on the cytogenctic and genetic aspects of MCC. There is no report on the gene expression profile of MCC. Thus there is a need, for both scientific and clinical reasons, to identify genes and pathways that are involved in the development and progression of MCC. We analyzed the gene expression profile of MCC by the microarray technique. Forty-four genes were upregulated and 149 genes were downregulated in MCC. Differential expression data were confirmed for 5 genes by semiquantitative RT-PCR in MCC tumors: GTF2H4, RBM12, UBE2D3, DDX17, and LZTS1. We found dysregulation of two major pathways in MCC: MAPK and JAK/STAT. Clusters of genes on chromosomes 1, 12, and 19 were dysregUlated in MCC. The data presented here will facilitate the identification of specific markers and therapeutic targets for the treatment of MCC patients. (c) 2007 Elsevier Inc. All rights reserved.

Molecular analysis of Friedreich's ataxia locus in the Indian population

Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by expansion of GAA repeats in the frataxin gene. We have carried out the first molecular analysis at the Friedreich's ataxia locus in the Indian population. Materials and methods - Three families clinically diagnosed for Friedreich's ataxia were analyzed for GAA expansion at the FRDA locus. The distribution of GAA repeats was also estimated in normal individuals of Indian origin. Results - All patients clinically diagnosed for Friedreich's ataxia were found to be homozygous for GAA repeat expansion. The GAA repeat in the normal population show a bimodal distribution with 94% of alleles ranging from 7-16 repeats. Conclusion - Indian patients with expansion at the FRDA locus showed typical clinical features of Friedreich's ataxia. The low frequency of large normal alleles (6%) could indicate that the prevalence of this disease in the Indian population is likely to be low.

Lectin Microarrays for Glycomic Analysis

Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glycocode. Several tools are being developed for glycan profiling based on chromatography,m mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins.

Copper, Zinc-Superoxide Dismutase from Clinically Isolated Escherichia coli: Cloning, Analysis of sodC and Its Possible Role in Pathogenicity

Superoxide dismutase has been discovered within the periplasm of several Gram-negative pathogens. We studied the Cu,Zn-SOD enzyme in Escherichia coli isolated from clinical samples (stool samples) collected from patients suffering from diarrhea. Antibiogram studies of the isolates were carried out to determine the sensitive and resistant strains. The metal co-factor present in the enzyme was confirmed by running samples in native gels and inhibiting with 2 mM potassium cyanide. A 519 bp sodC gene was amplified from resistant and sensitive strains of Escherichia coli. Cloning and sequencing of the sodC gene indicated variation in the protein and amino acid sequences of sensitive and resistant isolates. The presence of sodC in highly resistant Escherichia coli isolates from diarrheal patients indicates that sodC may play role in enhancing the pathogenicity by protecting cells from exogenous sources of superoxide, such as the oxidative burst of phagocytes. The presence of SodC could be one of the factors for bacterial virulence.

Clinical Proteomics of the Neglected Human Malarial Parasite Plasmodium vivax

Recent reports highlight the severity and the morbidity of disease caused by the long neglected malaria parasite Plasmodium vivax. Due to inherent difficulties in the laboratory-propagation of P. vivax, the biology of this parasite has not been adequately explored. While the proteome of P. falciparum, the causative agent of cerebral malaria, has been extensively explored from several sources, there is limited information on the proteome of P. vivax. We have, for the first time, examined the proteome of P. vivax isolated directly from patients without adaptation to laboratory conditions. We have identified 153 proteins from clinical P. vivax, majority of which do not show homology to any previously known gene products. We also report 29 new proteins that were found to be expressed in P. vivax for the first time. In addition, several proteins previously implicated as anti-malarial targets, were also found in our analysis. Most importantly, we found several unique proteins expressed by P. vivax. This study is an important step in providing insight into physiology of the parasite under clinical settings.

Fourier descriptors for morphological analysis of vectorcardiograms

The use of Fourier shape descriptors for morphological studies of vectorcardio-grams (VCGs) is p resented . The FDs can effectively be used as features for classf-fication of VCGs of different clinical categories . In addition , they provide cli-nically significant qualitative shape information for use by the Cardiologist. The initial result sofanalysisof nwrmal and abnormal VCGs areencouraging.

Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

Clinical phenotype and the lack of mutations in the CHRNG, CHRND, and CHRNA1 genes in two Indian families with Escobar syndrome

The objective of this study was to report the clinical phenotype and genetic analysis of two Indian families with Escobar syndrome (ES). The diagnosis of ES in both families was made on the basis of published clinical features. Blood samples were collected from members of both families and used in genomic DNA isolation. The entire coding regions and intron-exon junctions of the ES gene CHRNG (cholinergic receptor, nicotinic, gamma), and two other related genes, CHRND and CHRNA1, were amplified and sequenced to search for mutations in both families. Both families show a typical form of ES. Sequencing of the entire coding regions including the intron-exon junctions of the three genes did not yield any mutations in these families. In conclusion, it is possible that the mutations in these genes are located in the promoter or deep intronic regions that we failed to identify or the ES in these families is caused by mutations in a different gene. The lack of mutations in CHRNG has also been reported in several families, suggesting the possibility of at least one more gene for this syndrome. Clin Dysmorphol 22:54-58 (C) 2013 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

Indigenous Development of an Imaging Flow Cytometer for Clinical and Biological Applications

Flow cytometry is a benchmark technique used for basic research and clinical diagnosis of various diseases. Despite being a high-throughput technique, it fails in capturing the morphology of cells being analyzed. Imaging flow cytometry is a combination of flow-cytometry and digital microscopy, which offers advantages of both the techniques. In this paper, we report on the development of an indigenous Imaging Flow Cytometer, realized with the combination of Optics, Microfluidics, and High-speed imaging. A custom-made bright-field transmission microscope is used to capture images of cells flowing across the microfluidic device. High-throughput morphological analysis on suspension of yeast cells is presented.

Lesion Detection in Breast Ultrasound Images Using Tissue Transition Analysis

Breast cancer is one of the leading cause of cancer related deaths in women and early detection is crucial for reducing mortality rates. In this paper, we present a novel and fully automated approach based on tissue transition analysis for lesion detection in breast ultrasound images. Every candidate pixel is classified as belonging to the lesion boundary, lesion interior or normal tissue based on its descriptor value. The tissue transitions are modeled using a Markov chain to estimate the likelihood of a candidate lesion region. Experimental evaluation on a clinical dataset of 135 images show that the proposed approach can achieve high sensitivity (95 %) with modest (3) false positives per image. The approach achieves very similar results (94 % for 3 false positives) on a completely different clinical dataset of 159 images without retraining, highlighting the robustness of the approach.

The influence of reduced oxygen availability on gene expression in laboratory (H37Rv) and clinical strains (S7 and S10) of Mycobacterium tuberculosis

Mycobacterium tuberculosis has the ability to persist within the host in a dormant stage. One important condition believed to contribute to dormancy is reduced access to oxygen known as hypoxia. However, the response of M. tuberculosis to such hypoxia condition is not fully characterized. Virtually all dormant models against tuberculosis tested in animals used laboratory strain H37Rv or Erdman strain. But major outbreaks of tuberculosis (TB) occur with the strains that have widely different genotypes and phenotypes compared to H37Rv. In this study, we used a custom oligonucleotide microarray to determine the overall transcriptional response of laboratory strain (H37Rv) and most prevalent clinical strains (S7 and S10) of M. tuberculosis from South India to hypoxia. Analysis of microarray results revealed that a total of 1161 genes were differentially regulated (>= 1.5 fold change) in H37Rv, among them 659 genes upregulated and 502 genes down regulated. Microarray data of clinical isolates showed that a total of 790 genes were differentially regulated in S7 among which 453 genes were upregulated and 337 down regulated. Interestingly, numerous genes were also differentially regulated in S10 (total 2805 genes) of which 1463 genes upregulated and 1342 genes down regulated during reduced oxygen condition (Wayne's model). One hundred and thirty-four genes were found common and upregulated among all three strains (H37Rv, S7, and S10) and can be targeted for drug/vaccine development against TB. (C) 2015 Published by Elsevier B.V.

Analysis of five glucometers available in India

In this study, we report on the accuracy, precision and clinical acceptability of the five blood glucose meters available in India. Glucose levels of 100 blood samples were measured with each meter, at IISc health centre laboratory under same conditions and the results were compared with laboratory reference standard. In order to calculate the coefficient of variation (CV), each sample was tested three times. None of the glucometer showed 100 % compliance on CV measure. In terms of accuracy, none of the glucometer satisfied the most stringent ADA-1994 standard. In general all the glucometers showed improved accuracy with respect to the most relaxed ISO 1597:2003 standard. The Clarke error grid analysis was performed to assess the clinical acceptability of the glucometers. All five glucometers had more than 90 % of test results in Zone A and B. Bland-Altman analysis indicates that all glucometers show a positive bias, indicating that the measured values tend to be higher than the laboratory reference standard.