Towards Precision Medicine: Advances in Computational Approaches for the Analysis of Human Variants

Variations and similarities in our individual genomes are part of our history, our heritage, and our identity. Some human genomic variants are associated with common traits such as hair and eye color, while others are associated with susceptibility to disease or response to drug treatment. Identifying the human variations producing clinically relevant phenotypic changes is critical for providing accurate and personalized diagnosis, prognosis, and treatment for diseases. Furthermore, a better understanding of the molecular underpinning of disease can lead to development of new drug targets for precision medicine. Several resources have been designed for collecting and storing human genomic variations in highly structured, easily accessible databases. Unfortunately, a vast amount of information about these genetic variants and their functional and phenotypic associations is currently buried in the literature, only accessible by manual curation or sophisticated text text-mining technology to extract the relevant information. In addition, the low cost of sequencing technologies coupled with increasing computational power has enabled the development of numerous computational methodologies to predict the pathogenicity of human variants. This review provides a detailed comparison of current human variant resources, including HGMD, OMIM, ClinVar, and UniProt/Swiss-Prot, followed by an overview of the computational methods and techniques used to leverage the available data to predict novel deleterious variants. We expect these resources and tools to become the foundation for understanding the molecular details of genomic variants leading to disease, which in turn will enable the promise of precision medicine.     

Performance evaluation of a new algorithm for the detection of remote homologs with sequence comparison

A detailed analysis of the performance of hybrid, a new sequence alignment algorithm developed by Yu and coworkers that combines Smith Waterman local dynamic programming with a local version of the maximum-likelihood approach, was made to access the applicability of this algorithm to the detection of distant homologs by sequence comparison. We analyzed the statistics of hybrid with a set of nonhomologous protein sequences from the SCOP database and found that the statistics of the scores from hybrid algorithm follows an Extreme Value Distribution with lambda approximately 1, as previously shown by Yu et al. for the case of artificially generated sequences. Local dynamic programming was compared to the hybrid algorithm by using two different test data sets of distant homologs from the PFAM and COGs protein sequence databases. The studies were made with several score functions in current use including OPTIMA, a new score function originally developed to detect remote homologs with the Smith Waterman algorithm. We found OPTIMA to be the best score function for both both dynamic programming and the hybrid algorithms. The ability of dynamic programming to discriminate between homologs and nonhomologs in the two sets of distantly related sequences is slightly better than that of hybrid algorithm. The advantage of producing accurate score statistics with only a few simulations may overcome the small differences in performance and make this new algorithm suitable for detection of homologs in conjunction with a wide range of score functions and gap penalties.     

Independence of Evoked Vocal Responses from Stimulus Direction in Burrowing Frogs Eupsophus (Leptodactylidae)

Localization of a sound source is important for animals in mating contexts: females generally orient towards signalling males, and males can estimate the position and quality of potential rivals. In anurans, the effect of sound direction on evoked vocal responses has been studied in males of Rana catesbeiana, which alter their vocal responses depending on the location of the stimulus. The current study explored the effects of sound direction in Eupsophus calcaratus, a frog that calls from inside burrows having resonance that would hinder the localization of incoming sounds. The vocal responses of 11 males to synthetic imitations of the conspecific advertisement call broadcast from loudspeakers positioned in front, to the right and left from the burrow openings were similar in terms of call rate, duration and latency. The invariance of the vocal responses indicates that for burrowing male frogs engaged in chorusing behaviour, the specific location of an opponent does not alter the persistence of vocal activity.     

Surface-bound phosphatase activity in living hyphae of ectomycorrhizal fungi of Nothofagus obliqua

We determined the location and the activity of surface-bound phosphomonoesterase (SBP) of five ectomycorrhizal (EM) fungi of Nothofagus oblique. EM fungal mycelium of Paxillus involutus, Austropaxillus boletinoides, Descolea antartica, Cenococcum geophilum and Pisolithus tinctorius was grown in media with varying concentrations of dissolved phosphorus. SBP activity was detected at different pH values (3-7) under each growth regimen. SBP activity was assessed using a colorimetric method based on the hydrolysis of p-nitrophenyl phosphate (pNPP) to p-nitrophenol phosphate (pNP) + P. A new technique involving confocal laser-scanning microscopy (LSM) was used to locate and quantify SBP activity on the hyphal surface. EM fungi showed two fundamentally different patterns of SBP activity in relation to varying environmental conditions (P-concentrations and pH). In the cases of D. antartica, A. boletinoides and C. geophilum, changes in SBP activity were induced primarily by changes in the number of SBP-active centers on the hyphae. In the cases of P. tinctorius and P. involutus, the number of SBP-active centers per μm hyphal length changed much less than the intensity of the SBP-active centers on the hyphae. Our findings not only contribute to the discussion about the role of SBP-active centers in EM fungi but also introduce LSM as a valuable method for studying EM fungi.     

The spatial distribution of acid phosphatase activity in ectomycorrhizal tissues depends on soil fertility and morphotype, and relates to host plant phosphorus uptake

Acid phosphatase (ACP) enzymes are involved in the mobilization of soil phosphorus (P) and polyphosphate accumulated in the fungal tissues of ectomycorrhizal roots, thereby influencing the amounts of P that are stored in the fungus and transferred to the host plant. This study evaluated the effects of ectomycorrhizal morphotype and soil fertility on ACP activity in the extraradical mycelium (ACP(myc)), the mantle (ACP(mantle)) and the Hartig net region (ACP(Hartig)) of ectomycorrhizal Nothofagus obliqua seedlings. ACP activity was quantified in vivo using enzyme-labelled fluorescence-97 (ELF-97) substrate, confocal laser microscopy and digital image processing routines. There was a significant effect of ectomycorrhizal morphotype on ACP(myc), ACP(mantle) and ACP(Hartig), while soil fertility had a significant effect on ACP(myc) and ACP(Hartig). The relative contribution of the mantle and the Hartig net region to the ACP activity on the ectomycorrhizal root was significantly affected by ectomycorrhizal morphotype and soil fertility. A positive correlation between ACP(Hartig) and the shoot P concentration was found, providing evidence that ACP activity at the fungus:root interface is involved in P transfer from the fungus to the host. It is concluded that the spatial distribution of ACP in ectomycorrhizas varies as a function of soil fertility and colonizing fungus.     

Chapter 4: Protein Interactions and Disease

Proteins do not function in isolation; it is their interactions with one another and also with other molecules (e.g. DNA, RNA) that mediate metabolic and signaling pathways, cellular processes, and organismal systems. Due to their central role in biological function, protein interactions also control the mechanisms leading to healthy and diseased states in organisms. Diseases are often caused by mutations affecting the binding interface or leading to biochemically dysfunctional allosteric changes in proteins. Therefore, protein interaction networks can elucidate the molecular basis of disease, which in turn can inform methods for prevention, diagnosis, and treatment. In this chapter, we will describe the computational approaches to predict and map networks of protein interactions and briefly review the experimental methods to detect protein interactions. We will describe the application of protein interaction networks as a translational approach to the study of human disease and evaluate the challenges faced by these approaches.

What to Learn in This Chapter

• Experimental and computational methods to detect protein interactions
• Protein networks and disease
• Studying the genetic and molecular basis of disease
• Using protein interactions to understand disease

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Structure and Spatial‐Temporal Dynamics of Chironomidae Fauna (Diptera) in Upland and Lowland Fluvial Habitats of the Chocancharava River Basin (Argentina)

Structure of benthic Chironomidae assemblages and their spatial‐temporal dynamic were analyzed in upland and lowland habitats from the Chocancharava River basin (Córdoba, Argentina). Sampling was performed in three tributary streams and in three lowland reaches of the river during high and low rainfall periods. Characteristic taxa of upland and lowland reaches and of the different habitats in these reaches were identified using the IndVal method. Chironomidae assemblages were different between upland and lowland reaches and among habitats in each reach, as assessed by Multiresponse Permutation Procedure and Canonical Correspondence Analyses. Substrate type and current velocity were the major explanatory variables structuring the assemblages in upland reaches whereas in lowland reaches current velocity and aquatic vegetation were the most important variables. The highest richness was found in the most complex habitat units in both upland and lowland stretches as assessed by Analyses of Variance. Chironomidae larvae responded to longitudinal changes of hydraulic variables and to local variations of fluvial habitats at different reaches. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Building Capacity in Central Havana to Sustainably Manage Environmental Health Risk in an Urban Ecosystem

In the late 1990s, community officials in the inner city neighborhood of Central Havana consulted researchers at INHEM (National Institute of Hygiene, Epidemiology, and Microbiology) for assistance in evaluating the effectiveness of interventions that were being undertaken to improve the quality of life and human health amid the severe economic crisis that Cuba was experiencing. The ecosystem approach to human health framework was applied through a Cuban–Canadian collaboration to assess whether the measures taken to improve housing, municipal infrastructure, and social and cultural life were effective, and to strengthen local capacity to manage environmental health risks. Household surveys, interviews, and a series of workshops and meetings conducted between 1999 and 2001 indicated that the intervention had been effective and pointed to further needs. The greater capacity to understand and manage determinants of health led to the use of the Ecohealth framework being adopted to help respond to a serious outbreak of dengue fever in Havana in 2001–2002, as well as a follow-up project in 2003 to apply an integrated surveillance approach to more sustainably prevent and control future recurrences of dengue by extending established monitoring of clinical-epidemiological and entomological factors, linking this to more systematic monitoring and control of environmental conditions, and strengthening community participation. The experience in central Havana indicates that application of the Ecohealth framework can play a useful role in strengthening capacities for managing further challenges to a community.