Transcriptomic and proteomic analyses of the Aspergillus fumigatus hypoxia response using an oxygen-controlled fermenter

<p>Abstract</p> <p>Background</p> <p><it>Aspergillus fumigatus </it>is a mold responsible for the majority of cases of aspergillosis in humans. To survive in the human body, <it>A. fumigatus </it>must adapt to microenvironments that are often characterized by low nutrient and oxygen availability. Recent research suggests that the ability of <it>A. fumigatus </it>and other pathogenic fungi to adapt to hypoxia contributes to their virulence. However, molecular mechanisms of <it>A. fumigatus </it>hypoxia adaptation are poorly understood. Thus, to better understand how <it>A. fumigatus </it>adapts to hypoxic microenvironments found <it>in vivo </it>during human fungal pathogenesis, the dynamic changes of the fungal transcriptome and proteome in hypoxia were investigated over a period of 24 hours utilizing an oxygen-controlled fermenter system.</p> <p>Results</p> <p>Significant increases in transcripts associated with iron and sterol metabolism, the cell wall, the GABA shunt, and transcriptional regulators were observed in response to hypoxia. A concomitant reduction in transcripts was observed with ribosome and terpenoid backbone biosynthesis, TCA cycle, amino acid metabolism and RNA degradation. Analysis of changes in transcription factor mRNA abundance shows that hypoxia induces significant positive and negative changes that may be important for regulating the hypoxia response in this pathogenic mold. Growth in hypoxia resulted in changes in the protein levels of several glycolytic enzymes, but these changes were not always reflected by the corresponding transcriptional profiling data. However, a good correlation overall (R²= 0.2, p < 0.05) existed between the transcriptomic and proteomics datasets for all time points. The lack of correlation between some transcript levels and their subsequent protein levels suggests another regulatory layer of the hypoxia response in <it>A. fumigatus</it>.</p> <p>Conclusions</p> <p>Taken together, our data suggest a robust cellular response that is likely regulated both at the transcriptional and post-transcriptional level in response to hypoxia by the human pathogenic mold <it>A. fumigatus</it>. As with other pathogenic fungi, the induction of glycolysis and transcriptional down-regulation of the TCA cycle and oxidative phosphorylation appear to major components of the hypoxia response in this pathogenic mold. In addition, a significant induction of the transcripts involved in ergosterol biosynthesis is consistent with previous observations in the pathogenic yeasts <it>Candida albicans </it>and <it>Cryptococcus neoformans </it>indicating conservation of this response to hypoxia in pathogenic fungi. Because ergosterol biosynthesis enzymes also require iron as a co-factor, the increase in iron uptake transcripts is consistent with an increased need for iron under hypoxia. However, unlike <it>C. albicans </it>and <it>C. neoformans</it>, the GABA shunt appears to play an important role in reducing NADH levels in response to hypoxia in <it>A. fumigatus </it>and it will be intriguing to determine whether this is critical for fungal virulence. Overall, regulatory mechanisms of the <it>A. fumigatus </it>hypoxia response appear to involve both transcriptional and post-transcriptional control of transcript and protein levels and thus provide candidate genes for future analysis of their role in hypoxia adaptation and fungal virulence.</p

Comparative Genomics of Cryptosporidium

Until recently, the apicomplexan parasites, Cryptosporidium hominis andC. parvum, were considered the same species. However, the two parasites, now considered distinct species, exhibit significant differences in host range, infectivity, and pathogenicity, and their sequenced genomes exhibit only 95–97% identity. The availability of the complete genome sequences of these organisms provides the potential to identify the genetic variations that are responsible for the phenotypic differences between the two parasites. We compared the genome organization and structure, gene composition, the metabolic and other pathways, and the local sequence identity between the genes of these two Cryptosporidium species. Our observations show that the phenotypic differences between C. hominisand C. parvum are not due to gross genome rearrangements, structural alterations, gene deletions or insertions, metabolic capabilities, or other obvious genomic alterations. Rather, the results indicate that these genomes exhibit a remarkable structural and compositional conservation and suggest that the phenotypic differences observed are due to subtle variations in the sequences of proteins that act at the interface between the parasite and its host

A PAX5-OCT4-PRDM1 developmental switch specifies human primordial germ cells.

Dysregulation of genetic pathways during human germ cell development leads to infertility. Here, we analysed bona fide human primordial germ cells (hPGCs) to probe the developmental genetics of human germ cell specification and differentiation. We examined the distribution of OCT4 occupancy in hPGCs relative to human embryonic stem cells (hESCs). We demonstrated that development, from pluripotent stem cells to germ cells, is driven by switching partners with OCT4 from SOX2 to PAX5 and PRDM1. Gain- and loss-of-function studies revealed that PAX5 encodes a critical regulator of hPGC development. Moreover, an epistasis analysis indicated that PAX5 acts upstream of OCT4 and PRDM1. The PAX5-OCT4-PRDM1 proteins form a core transcriptional network that activates germline and represses somatic programmes during human germ cell differentiation. These findings illustrate the power of combined genome editing, cell differentiation and engraftment for probing human developmental genetics that have historically been difficult to study

Structural correlations in bacterial metabolic networks

<p>Abstract</p> <p>Background</p> <p>Evolution of metabolism occurs through the acquisition and loss of genes whose products acts as enzymes in metabolic reactions, and from a presumably simple primordial metabolism the organisms living today have evolved complex and highly variable metabolisms. We have studied this phenomenon by comparing the metabolic networks of 134 bacterial species with known phylogenetic relationships, and by studying a neutral model of metabolic network evolution.</p> <p>Results</p> <p>We consider the 'union-network' of 134 bacterial metabolisms, and also the union of two smaller subsets of closely related species. Each reaction-node is tagged with the number of organisms it belongs to, which we denote organism degree (OD), a key concept in our study. Network analysis shows that common reactions are found at the centre of the network and that the average OD decreases as we move to the periphery. Nodes of the same OD are also more likely to be connected to each other compared to a random OD relabelling based on their occurrence in the real data. This trend persists up to a distance of around five reactions. A simple growth model of metabolic networks is used to investigate the biochemical constraints put on metabolic-network evolution. Despite this seemingly drastic simplification, a 'union-network' of a collection of unrelated model networks, free of any selective pressure, still exhibit similar structural features as their bacterial counterpart.</p> <p>Conclusions</p> <p>The OD distribution quantifies topological properties of the evolutionary history of bacterial metabolic networks, and lends additional support to the importance of horizontal gene transfer during bacterial metabolic evolution where new reactions are attached at the periphery of the network. The neutral model of metabolic network growth can reproduce the main features of real networks, but we observe that the real networks contain a smaller common core, while they are more similar at the periphery of the network. This suggests that natural selection and biochemical correlations can act both to diversify and to narrow down metabolic evolution.</p

Connections between Classical and Parametric Network Entropies

This paper explores relationships between classical and parametric measures of graph (or network) complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity

Simple molecular networks that respond optimally to time-periodic stimulation

<p>Abstract</p> <p>Background</p> <p>Bacteria or cells receive many signals from their environment and from other organisms. In order to process this large amount of information, Systems Biology shows that a central role is played by regulatory networks composed of genes and proteins. The objective of this paper is to present and to discuss simple regulatory network motifs having the property to maximize their responses under time-periodic stimulations. In elucidating the mechanisms underlying these responses through simple networks the goal is to pinpoint general principles which optimize the oscillatory responses of molecular networks.</p> <p>Results</p> <p>We took a look at basic network motifs studied in the literature such as the Incoherent Feedforward Loop (IFFL) or the interlerlocked negative feedback loop. The former is also generalized to a diamond pattern, with network components being either purely genetic or combining genetic and signaling pathways. Using standard mathematics and numerical simulations, we explain the types of responses exhibited by the IFFL with respect to a train of periodic pulses. We show that this system has a non-vanishing response only if the inter-pulse interval is above a threshold. A slight generalisation of the IFFL (the diamond) is shown to work as an ideal pass-band filter. We next show a mechanism by which average of oscillatory response can be maximized by bursting temporal patterns. Finally we study the interlerlocked negative feedback loop, i.e. a 2-gene motif forming a loop where the nodes respectively activate and repress each other, and show situations where this system possesses a resonance under periodic stimulation.</p> <p>Conclusion</p> <p>We present several simple motif designs of molecular networks producing optimal output in response to periodic stimulations of the system. The identified mechanisms are simple and based on known network motifs in the literature, so that that they could be embodied in existing organisms, or easily implementable by means of synthetic biology. Moreover we show that these designs can be studied in different contexts of molecular biology, as for example in genetic networks or in signaling pathways.</p

Optimized ancestral state reconstruction using Sankoff parsimony

<p>Abstract</p> <p>Background</p> <p>Parsimony methods are widely used in molecular evolution to estimate the most plausible phylogeny for a set of characters. Sankoff parsimony determines the minimum number of changes required in a given phylogeny when a cost is associated to transitions between character states. Although optimizations exist to reduce the computations in the number of taxa, the original algorithm takes time <it>O</it>(<it>n</it>²) in the number of states, making it impractical for large values of <it>n</it>.</p> <p>Results</p> <p>In this study we introduce an optimization of Sankoff parsimony for the reconstruction of ancestral states when ultrametric or additive cost matrices are used. We analyzed its performance for randomly generated matrices, Jukes-Cantor and Kimura's two-parameter models of DNA evolution, and in the reconstruction of elongation factor-1<it>α </it>and ancestral metabolic states of a group of eukaryotes, showing that in all cases the execution time is significantly less than with the original implementation.</p> <p>Conclusion</p> <p>The algorithms here presented provide a fast computation of Sankoff parsimony for a given phylogeny. Problems where the number of states is large, such as reconstruction of ancestral metabolism, are particularly adequate for this optimization. Since we are reducing the computations required to calculate the parsimony cost of a single tree, our method can be combined with optimizations in the number of taxa that aim at finding the most parsimonious tree.</p

Modeling protein network evolution under genome duplication and domain shuffling

<p>Abstract</p> <p>Background</p> <p>Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such <it>exponential </it>evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI) networks by outweighing, in particular, all <it>time-linear </it>network growths modeled so far.</p> <p>Results</p> <p>We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from <it>i) </it>prevailing <it>exponential </it>network dynamics under duplication and <it>ii) asymmetric divergence </it>of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of <it>direct </it>and <it>indirect </it>PPI networks of <it>S. cerevisiae </it>are well reproduced numerically with only two adjusted parameters of clear biological significance (<it>i.e</it>. network effective growth rate and average number of protein-binding domains per protein).</p> <p>Conclusion</p> <p>This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale-free topologies of PPI networks, which are found to be robust to extensive shuffling of protein domains, appear to be a simple consequence of the conservation of protein-binding domains under asymmetric duplication/divergence dynamics in the course of evolution.</p

SREBP Coordinates Iron and Ergosterol Homeostasis to Mediate Triazole Drug and Hypoxia Responses in the Human Fungal Pathogen Aspergillus fumigatus

Sterol regulatory element binding proteins (SREBPs) are a class of basic helix-loop-helix transcription factors that regulate diverse cellular responses in eukaryotes. Adding to the recognized importance of SREBPs in human health, SREBPs in the human fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus are required for fungal virulence and susceptibility to triazole antifungal drugs. To date, the exact mechanism(s) behind the role of SREBP in these observed phenotypes is not clear. Here, we report that A. fumigatus SREBP, SrbA, mediates regulation of iron acquisition in response to hypoxia and low iron conditions. To further define SrbA's role in iron acquisition in relation to previously studied fungal regulators of iron metabolism, SreA and HapX, a series of mutants were generated in the ΔsrbA background. These data suggest that SrbA is activated independently of SreA and HapX in response to iron limitation, but that HapX mRNA induction is partially dependent on SrbA. Intriguingly, exogenous addition of high iron or genetic deletion of sreA in the ΔsrbA background was able to partially rescue the hypoxia growth, triazole drug susceptibility, and decrease in ergosterol content phenotypes of ΔsrbA. Thus, we conclude that the fungal SREBP, SrbA, is critical for coordinating genes involved in iron acquisition and ergosterol biosynthesis under hypoxia and low iron conditions found at sites of human fungal infections. These results support a role for SREBP–mediated iron regulation in fungal virulence, and they lay a foundation for further exploration of SREBP's role in iron homeostasis in other eukaryotes