Systems approaches applied to the study of Saccharomyces cerevisiae and Halobacterium sp

Online tools for bioinformatics analyses in nutrition sciences

Recent advances in "omics" research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field.

The plant proteome folding project: structure and positive selection in plant protein families

Despite its importance, relatively little is known about the relationship between the structure, function, and evolution of proteins, particularly in land plant species. We have developed a database with predicted protein domains for five plant proteomes (http://pfp.bio.nyu.edu) and used both protein structural fold recognition and de novo Rosetta-based protein structure prediction to predict protein structure for Arabidopsis and rice proteins. Based on sequence similarity, we have identified ∼15,000 orthologous/paralogous protein family clusters among these species and used codon-based models to predict positive selection in protein evolution within 175 of these sequence clusters. Our results show that codons that display positive selection appear to be less frequent in helical and strand regions and are overrepresented in amino acid residues that are associated with a change in protein secondary structure. Like in other organisms, disordered protein regions also appear to have more selected sites. Structural information provides new functional insights into specific plant proteins and allows us to map positively selected amino acid sites onto protein structures and view these sites in a structural and functional context.

Learning global models of transcriptional regulatory networks from data

Organisms must continually adapt to changing cellular and environmental factors (e.g., oxygen levels) by altering their gene expression patterns. At the same time, all organisms must have stable gene expression patterns that are robust to small fluctuations in environmental factors and genetic variation. Learning and characterizing the structure and dynamics of Regulatory Networks (RNs), on a whole-genome scale, is a key problem in systems biology. Here, we review the challenges associated with inferring RNs in a solely data-driven manner, concisely discuss the implications and contingencies of possible procedures that can be used, specifically focusing on one such procedure, the Inferelator. Importantly, the Inferelator explicitly models the temporal component of regulation, can learn the interactions between transcription factors and environmental factors, and attaches a statistically meaningful weight to every edge. The result of the Inferelator is a dynamical model of the RN that can be used to model the time-evolution of cell state.

A personal journey of discovery: developing technology and changing biology

This autobiographical article describes my experiences in developing chemically based, biological technologies for deciphering biological information: DNA, RNA, proteins, interactions, and networks. The instruments developed include protein and DNA sequencers and synthesizers, as well as ink-jet technology for synthesizing DNA chips. Diverse new strategies for doing biology also arose from novel applications of these instruments. The functioning of these instruments can be integrated to generate powerful new approaches to cloning and characterizing genes from a small amount of protein sequence or to using gene sequences to synthesize peptide fragments so as to characterize various properties of the proteins. I also discuss the five paradigm changes in which I have participated: the development and integration of biological instrumentation; the human genome project; cross-disciplinary biology; systems biology; and predictive, personalized, preventive, and participatory (P4) medicine. Finally, I discuss the origins, the philosophy, some accomplishments, and the future trajectories of the Institute for Systems Biology.

A systems view of haloarchaeal strategies to withstand stress from transition metals

Given that transition metals are essential cofactors in central biological processes, misallocation of the wrong metal ion to a metalloprotein can have resounding and often detrimental effects on diverse aspects of cellular physiology. Therefore, in an attempt to characterize unique and shared responses to chemically similar metals, we have reconstructed physiological behaviors of Halobacterium NRC-1, an archaeal halophile, in sublethal levels of Mn(II), Fe(II), Co(II), Ni(II), Cu(II), and Zn(II). Over 20% of all genes responded transiently within minutes of exposure to Fe(II), perhaps reflecting immediate large-scale physiological adjustments to maintain homeostasis. At steady state, each transition metal induced growth arrest, attempts to minimize oxidative stress, toxic ion scavenging, increased protein turnover and DNA repair, and modulation of active ion transport. While several of these constitute generalized stress responses, up-regulation of active efflux of Co(II), Ni(II), Cu(II), and Zn(II), down-regulation of Mn(II) uptake and up-regulation of Fe(II) chelation, confer resistance to the respective metals. We have synthesized all of these discoveries into a unified systems-level model to provide an integrated perspective of responses to six transition metals with emphasis on experimentally verified regulatory mechanisms. Finally, through comparisons across global transcriptional responses to different metals, we provide insights into putative in vivo metal selectivity of metalloregulatory proteins and demonstrate that a systems approach can help rapidly unravel novel metabolic potential and regulatory programs of poorly studied organisms.

A data integration methodology for systems biology: experimental verification

The integration of data from multiple global assays is essential to understanding dynamic spatiotemporal interactions within cells. In a companion paper, we reported a data integration methodology, designated Pointillist, that can handle multiple data types from technologies with different noise characteristics. Here we demonstrate its application to the integration of 18 data sets relating to galactose utilization in yeast. These data include global changes in mRNA and protein abundance, genome-wide protein-DNA interaction data, database information, and computational predictions of protein-DNA and protein-protein interactions. We divided the integration task to determine three network components: key system elements (genes and proteins), protein-protein interactions, and protein-DNA interactions. Results indicate that the reconstructed network efficiently focuses on and recapitulates the known biology of galactose utilization. It also provided new insights, some of which were verified experimentally. The methodology described here, addresses a critical need across all domains of molecular and cell biology, to effectively integrate large and disparate data sets.

Genome sequence of Haloarcula marismortui: a halophilic archaeon from the Dead Sea

We report the complete sequence of the 4,274,642-bp genome of Haloarcula marismortui, a halophilic archaeal isolate from the Dead Sea. The genome is organized into nine circular replicons of varying G+C compositions ranging from 54% to 62%. Comparison of the genome architectures of Halobacterium sp. NRC-1 and H. marismortui suggests a common ancestor for the two organisms and a genome of significantly reduced size in the former. Both of these halophilic archaea use the same strategy of high surface negative charge of folded proteins as means to circumvent the salting-out phenomenon in a hypersaline cytoplasm. A multitiered annotation approach, including primary sequence similarities, protein family signatures, structure prediction, and a protein function association network, has assigned putative functions for at least 58% of the 4242 predicted proteins, a far larger number than is usually achieved in most newly sequenced microorganisms. Among these assigned functions were genes encoding six opsins, 19 MCP and/or HAMP domain signal transducers, and an unusually large number of environmental response regulators-nearly five times as many as those encoded in Halobacterium sp. NRC-1--suggesting H. marismortui is significantly more physiologically capable of exploiting diverse environments. In comparing the physiologies of the two halophilic archaea, in addition to the expected extensive similarity, we discovered several differences in their metabolic strategies and physiological responses such as distinct pathways for arginine breakdown in each halophile. Finally, as expected from the larger genome, H. marismortui encodes many more functions and seems to have fewer nutritional requirements for survival than does Halobacterium sp. NRC-1.

Systems biology and new technologies enable predictive and preventative medicine

Systems approaches to disease are grounded in the idea that disease-perturbed protein and gene regulatory networks differ from their normal counterparts; we have been pursuing the possibility that these differences may be reflected by multiparameter measurements of the blood. Such concepts are transforming current diagnostic and therapeutic approaches to medicine and, together with new technologies, will enable a predictive and preventive medicine that will lead to personalized medicine.

Systems level insights into the stress response to UV radiation in the halophilic archaeon Halobacterium NRC-1

We report a remarkably high UV-radiation resistance in the extremely halophilic archaeon Halobacterium NRC-1 withstanding up to 110 J/m2 with no loss of viability. Gene knockout analysis in two putative photolyase-like genes (phr1 and phr2) implicated only phr2 in photoreactivation. The UV-response was further characterized by analyzing simultaneously, along with gene function and protein interactions inferred through comparative genomics approaches, mRNA changes for all 2400 genes during light and dark repair. In addition to photoreactivation, three other putative repair mechanisms were identified including d(CTAG) methylation-directed mismatch repair, four oxidative damage repair enzymes, and two proteases for eliminating damaged proteins. Moreover, a UV-induced down-regulation of many important metabolic functions was observed during light repair and seems to be a phenomenon shared by all three domains of life. The systems analysis has facilitated the assignment of putative functions to 26 of 33 key proteins in the UV response through sequence-based methods and/or similarities of their predicted three-dimensional structures to known structures in the PDB. Finally, the systems analysis has raised, through the integration of experimentally determined and computationally inferred data, many experimentally testable hypotheses that describe the metabolic and regulatory networks of Halobacterium NRC-1.