Rajeev K. Azad

ABA Is Required for Plant Acclimation to a Combination of Salt and Heat Stress

Abiotic stresses such as drought, heat or salinity are a major cause of yield loss worldwide. Recent studies revealed that the acclimation of plants to a combination of different environmental stresses is unique and cannot be directly deduced from studying the response of plants to each of the different stresses applied individually. Here we report on the response of Arabidopsis thaliana to a combination of salt and heat stress using transcriptome analysis, physiological measurements and mutants deficient in abscisic acid, salicylic acid, jasmonic acid or ethylene signaling. Arabidopsis plants were found to be more susceptible to a combination of salt and heat stress compared to each of the different stresses applied individually. The stress combination resulted in a higher ratio of Na+/K+ in leaves and caused the enhanced expression of 699 transcripts unique to the stress combination. Interestingly, many of the transcripts that specifically accumulated in plants in response to the salt and heat stress combination were associated with the plant hormone abscisic acid. In accordance with this finding, mutants deficient in abscisic acid metabolism and signaling were found to be more susceptible to a combination of salt and heat stress than wild type plants. Our study highlights the important role abscisic acid plays in the acclimation of plants to a combination of two different abiotic stresses.

Detecting laterally transferred genes: use of entropic clustering methods and genome position

Most parametric methods for detecting foreign genes in bacterial genomes use a scoring function that measures the atypicality of a gene with respect to the bulk of the genome. Genes whose features are sufficiently atypical—lying beyond a threshold value—are deemed foreign. Yet these methods fail when the range of features of donor genomes overlaps with that of the recipient genome, leading to misclassification of foreign and native genes; existing parametric methods choose threshold parameters to balance these error rates. To circumvent this problem, we have developed a two-pronged approach to minimize the misclassification of genes. First, beyond classifying genes as merely atypical, a gene clustering method based on Jensen–Shannon entropic divergence identifies classes of foreign genes that are also similar to each other. Second, genome position is used to reassign genes among classes whose composition features overlap. This process minimizes the misclassification of either native or foreign genes that are weakly atypical. The performance of this approach was assessed using artificial chimeric genomes and then applied to the well-characterized Escherichia coli K12 genome. Not only were foreign genes identified with a high degree of accuracy, but genes originating from the same donor organism were effectively grouped.

Use of Artificial Genomes in Assessing Methods for Atypical Gene Detection

Parametric methods for identifying laterally transferred genes exploit the directional mutational biases unique to each genome. Yet the development of new, more robust methods—as well as the evaluation and proper implementation of existing methods—relies on an arbitrary assessment of performance using real genomes, where the evolutionary histories of genes are not known. We have used the framework of a generalized hidden Markov model to create artificial genomes modeled after genuine genomes. To model a genome, “core” genes—those displaying patterns of mutational biases shared among large numbers of genes—are identified by a novel gene clustering approach based on the Akaike information criterion. Gene models derived from multiple “core” gene clusters are used to generate an artificial genome that models the properties of a genuine genome. Chimeric artificial genomes—representing those having experienced lateral gene transfer—were created by combining genes from multiple artificial genomes, and the performance of the parametric methods for identifying “atypical” genes was assessed directly. We found that a hidden Markov model that included multiple gene models, each trained on sets of genes representing the range of genotypic variability within a genome, could produce artificial genomes that mimicked the properties of genuine genomes. Moreover, different methods for detecting foreign genes performed differently—i.e., they had different sets of strengths and weaknesses—when identifying atypical genes within chimeric artificial genomes.

Detection of genomic islands via segmental genome heterogeneity

While the recognition of genomic islands can be a powerful mechanism for identifying genes that distinguish related bacteria, few methods have been developed to identify them specifically. Rather, identification of islands often begins with cataloging individual genes likely to have been recently introduced into the genome; regions with many putative alien genes are then examined for other features suggestive of recent acquisition of a large genomic region. When few phylogenetic relatives are available, the identification of alien genes relies on their atypical features relative to the bulk of the genes in the genome. The weakness of these ‘bottom–up’ approaches lies in the difficulty in identifying robustly those genes which are atypical, or phylogenetically restricted, due to recent foreign ancestry. Herein, we apply an alternative ‘top–down’ approach where bacterial genomes are recursively divided into progressively smaller regions, each with uniform composition. In this way, large chromosomal regions with atypical features are identified with high confidence due to the simultaneous analysis of multiple genes. This approach is based on a generalized divergence measure to quantify the compositional difference between segments in a hypothesis-testing framework. We tested the proposed genome island prediction algorithm on both artificial chimeric genomes and genuine bacterial genomes.

Current concepts in the pathogenesis and treatment of chronic suppurative otitis media.

Otitis media (OM) is an inflammation of the middle ear associated with infection. Despite appropriate therapy, acute OM (AOM) can progress to chronic suppurative OM (CSOM) associated with ear drum perforation and purulent discharge. The effusion prevents the middle ear ossicles from properly relaying sound vibrations from the ear drum to the oval window of the inner ear, causing conductive hearing loss. In addition, the inflammatory mediators generated during CSOM can penetrate into the inner ear through the round window. This can cause the loss of hair cells in the cochlea, leading to sensorineural hearing loss. Pseudomonas aeruginosa and Staphylococcus aureus are the most predominant pathogens that cause CSOM. Although the pathogenesis of AOM is well studied, very limited research is available in relation to CSOM. With the emergence of antibiotic resistance as well as the ototoxicity of antibiotics and the potential risks of surgery, there is an urgent need to develop effective therapeutic strategies against CSOM. This warrants understanding the role of host immunity in CSOM and how the bacteria evade these potent immune responses. Understanding the molecular mechanisms leading to CSOM will help in designing novel treatment modalities against the disease and hence preventing the hearing loss.

Towards more robust methods of alien gene detection

Because the properties of horizontally-transferred genes will reflect the mutational proclivities of their donor genomes, they often show atypical compositional properties relative to native genes. Parametric methods use these discrepancies to identify bacterial genes recently acquired by horizontal transfer. However, compositional patterns of native genes vary stochastically, leaving no clear boundary between typical and atypical genes. As a result, while strongly atypical genes are readily identified as alien, genes of ambiguous character are poorly classified when a single threshold separates typical and atypical genes. This limitation affects all parametric methods that examine genes independently, and escaping it requires the use of additional genomic information. We propose that the performance of all parametric methods can be improved by using a multiple-threshold approach. First, strongly atypical alien genes and strongly typical native genes would be identified using conservative thresholds. Genes with ambiguous compositional features would then be classified by examining gene context, including the class (native or alien) of flanking genes. By including additional genomic information in a multiple-threshold framework, we observed a remarkable improvement in the performance of several popular, but algorithmically distinct, methods for alien gene detection.

Simplifying the mosaic description of DNA sequences.

By using the Jensen-Shannon divergence, genomic DNA can be divided into compositionally distinct domains through a standard recursive segmentation procedure. Each domain, while significantly different from its neighbors, may, however, share compositional similarity with one or more distant (non-neighboring) domains. We thus obtain a coarse-grained description of the given DNA string in terms of a smaller set of distinct domain labels. This yields a minimal domain description of a given DNA sequence, significantly reducing its organizational complexity. This procedure gives a new means of evaluating genomic complexity as one examines organisms ranging from bacteria to human. The mosaic organization of DNA sequences could have originated from the insertion of fragments of one genome (the parasite) inside another (the host), and we present numerical experiments that are suggestive of this scenario.

Ultra-fast alterations in mRNA levels uncover multiple players in light stress acclimation in plants

Summary The acclimation of plants to changes in light intensity requires rapid responses at several different levels. These include biochemical and biophysical responses as well as alterations in the steady‐state level of different transcripts and proteins. Recent studies utilizing promoter::reporter constructs suggested that transcriptional responses to changes in light intensity could occur within seconds, rates for which changes in mRNA expression are not routinely measured or functionally studied. To identify and characterize rapid changes in the steady‐state level of different transcripts in response to light stress we performed RNA sequencing analysis of Arabidopsis thaliana plants subjected to light stress. Here we report that mRNA accumulation of 731 transcripts occurs as early as 20–60 sec following light stress application, and that at least five of these early response transcripts play an important biological role in the acclimation of plants to light stress. More than 20% of transcripts accumulating in plants within 20–60 sec of initiation of light stress are H2O2‐ and ABA‐response transcripts, and the accumulation of several of these transcripts is inhibited by transcriptional inhibitors. In accordance with the association of rapid response transcripts with H2O2 and ABA signaling, a mutant impaired in ABA sensing (abi‐1) was found to be more tolerant to light stress, and the response of several of the rapid response transcripts was altered in mutants impaired in reactive oxygen metabolism. Our findings reveal that transcriptome reprogramming in plants could occur within seconds of initiation of abiotic stress and that this response could invoke known as well as unknown proteins and pathways.

Detecting Evolutionary Strata on the Human X Chromosome in the Absence of Gametologous Y-Linked Sequences

Mammalian sex chromosomes arose from a pair of homologous autosomes that differentiated into the X and Y chromosomes following a series of recombination suppression events between the X and Y. The stepwise recombination suppressions from the distal long arm to the distal short arm of the chromosomes are reflected as regions with distinct X-Y divergence, referred to as evolutionary strata on the X. All current methods for stratum detection depend on X-Y comparisons but are severely limited by the paucity of X-Y gametologs. We have developed an integrative method that combines a top-down, recursive segmentation algorithm with a bottom-up, agglomerative clustering algorithm to decipher compositionally distinct regions on the X, which reflect regions of unique X-Y divergence. In application to human X chromosome, our method correctly classified a concatenated set of 35 previously assayed X-linked gene sequences by evolutionary strata. We then extended our analysis, applying this method to the entire sequence of the human X chromosome, in an effort to define stratum boundaries. The boundaries of more recently formed strata on X-added region, namely the fourth and fifth strata, have been defined by previous studies and are recapitulated with our method. The older strata, from the first up to the third stratum, have remained poorly resolved due to paucity of X-Y gametologs. By analyzing the entire X sequence, our method identified seven evolutionary strata in these ancient regions, where only three could previously be assayed, thus demonstrating the robustness of our method in detecting the evolutionary strata.

Activation of apoptosis in NAF-1-deficient human epithelial breast cancer cells.

ABSTRACT Maintaining iron (Fe) ion and reactive oxygen species homeostasis is essential for cellular function, mitochondrial integrity and the regulation of cell death pathways, and is recognized as a key process underlying the molecular basis of aging and various diseases, such as diabetes, neurodegenerative diseases and cancer. Nutrient-deprivation autophagy factor 1 (NAF-1; also known as CISD2) belongs to a newly discovered class of Fe-sulfur proteins that are localized to the outer mitochondrial membrane and the endoplasmic reticulum. It has been implicated in regulating homeostasis of Fe ions, as well as the activation of autophagy through interaction with BCL-2. Here we show that small hairpin (sh)RNA-mediated suppression of NAF-1 results in the activation of apoptosis in epithelial breast cancer cells and xenograft tumors. Suppression of NAF-1 resulted in increased uptake of Fe ions into cells, a metabolic shift that rendered cells more susceptible to a glycolysis inhibitor, and the activation of cellular stress pathways that are associated with HIF1α. Our studies suggest that NAF-1 is a major player in the metabolic regulation of breast cancer cells through its effects on cellular Fe ion distribution, mitochondrial metabolism and the induction of apoptosis. Summary: NAF-1 is a major player in the metabolic regulation of breast cancer cells through its effects on cellular Fe ion distribution, mitochondrial metabolism and the induction of apoptosis.