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Cells of most bacterial species are around 2 µm in length, with some of the largest specimens reaching 750 µm. Using fluorescence, x-ray, and electron microscopy in conjunction with genome sequencing, we characterized Ca. Thiomargarita magnifica, a bacterium with an average cell length greater than 9,000 µm that is visible to the naked eye. We found that these cells grow orders of magnitude over theoretical limits for bacterial cell size through unique biology, display unprecedented polyploidy of more than half a million copies of a very large genome, and undergo a dimorphic life cycle with asymmetric segregation of chromosomes in daughter cells. These features, along with compartmentalization of genomic material and protein synthesis in membrane-bound organelles, indicate gain of complexity in the Thiomargarita lineage, and challenge traditional concepts of bacterial cells.One Sentence SummaryCa. T. magnifica are compartmentalized centimeter-long bacteria

Symbiotic relationships between heterotrophic and phototrophic partners are common in microbial eukaryotes. Among Arcellinida (Amoebozoa) several species are associated with microalgae of the genus Chlorella (Archaeplastida). So far, these symbioses were assumed to be stable and mutualistic, yet details of the interactions are limited. Here, we analyzed 22 single-cell transcriptomes and 36 partially-sequenced genomes of the Arcellinida morphospecies Hyalosphenia papilio, which contains Chlorella algae, to shed light on the amoeba-algae association. By characterizing the genetic diversity of associated Chlorella, we detected two distinct clades that can be linked to host genetic diversity, yet at the same time show a biogeographic signal across sampling sites. Fluorescence and transmission electron microscopy showed the presence of intact algae cells within the amoeba cell. Yet analysis of transcriptome data suggested that the algal nuclei are inactive, implying that instead of a stable, mutualistic relationship, the algae may be temporarily exploited for photosynthetic activity before being digested. Differences in gene expression of H. papilio and Hyalosphenia elegans demonstrated increased expression of genes related to oxidative stress. Together, our analyses increase knowledge of this host-symbiont association and reveal 1) higher diversity of associated algae than previously characterized, 2) a transient association between H. papilio and Chlorella with unclear benefits for the algae, 3) algal-induced gene expression changes in the host.

Single-cell genomics (SCG) methods provide a unique opportunity to analyse whole genome information at the resolution of an individual cell. While SCG has been extensively used to investigate bacterial and archaeal genomes, the technique has been rarely used to access the genetic makeup of uncultivated microbial eukaryotes. In this regard, the use of SCG can provide a wealth of information; not only do the methods allow exploration of the genome, they can also help elucidate the relationship between the cell and intracellular entities extant in nearly all eukaryotes. SCG enables the study of total eukaryotic cellular DNA, which in turn allows us to better understand the evolutionary history and diversity of life, and the physiological interactions that define complex organisms. This article is part of a discussion meeting issue ‘Single cell ecology’.

De novo guanine biosynthesis is an evolutionarily conserved pathway that creates sufficient nucleotides to support DNA replication, transcription, and translation. Bacteria can also salvage nutrients from the environment to supplement the de novo pathway, but the relative importance of either pathway during Staphylococcus aureus infection is not known. In S. aureus , genes important for both de novo and salvage pathways are regulated by a guanine riboswitch. Bacterial riboswitches have attracted attention as a novel class of antibacterial drug targets because they have high affinity for small molecules, are absent in humans, and regulate the expression of multiple genes, including those essential for cell viability. Genetic and biophysical methods confirm the existence of a bona fide guanine riboswitch upstream of an operon encoding xanthine phosphoribosyltransferase ( xpt ), xanthine permease ( pbuX ), inosine-5′-monophosphate dehydrogenase ( guaB ), and GMP synthetase ( guaA ) that represses the expression of these genes in response to guanine. We found that S. aureus guaB and guaA are also transcribed independently of riboswitch control by alternative promoter elements. Deletion of xpt-pbuX-guaB-guaA genes resulted in guanine auxotrophy, failure to grow in human serum, profound abnormalities in cell morphology, and avirulence in mouse infection models, whereas deletion of the purine salvage genes xpt-pbuX had none of these effects. Disruption of guaB or guaA recapitulates the xpt-pbuX-guaB-guaA deletion in vivo . In total, the data demonstrate that targeting the guanine riboswitch alone is insufficient to treat S. aureus infections but that inhibition of guaA or guaB could have therapeutic utility. IMPORTANCE De novo guanine biosynthesis and purine salvage genes were reported to be regulated by a guanine riboswitch in Staphylococcus aureus . We demonstrate here that this is not true, because alternative promoter elements that uncouple the de novo pathway from riboswitch regulation were identified. We found that in animal models of infection, the purine salvage pathway is insufficient for S. aureus survival in the absence of de novo guanine biosynthesis. These data suggest targeting the de novo guanine biosynthesis pathway may have therapeutic utility in the treatment of S. aureus infections.

Many thousands of proteins encoded by the genome of Plasmodium falciparum, the causal organism of the deadliest form of human malaria, are of unknown function. It is of utmost importance that these proteins be characterized if we are to develop combative strategies against malaria based on the biology of the parasite. In an attempt to infer protein function on a genome-wide scale, we computationally modeled the P. falciparum interactome, elucidating local and global functional relationships between gene products. The resulting interaction network, reconstructed by integrating in silico and experimental functional genomics data within a Bayesian framework, covers ∼68% of the parasite genome and provides functional inferences for more than 2000 uncharacterized proteins, based on their associations. Network reconstruction involved the use of a novel strategy, where we incorporated continuously updated, uniform reference priors in our Bayesian model. This method for generating interaction maps is thus also well suited for application to other genomes, where pre-existing interactome knowledge is sparse. Additionally, we superimposed this map on genomes of three apicomplexan pathogens—Plasmodium yoelii,Toxoplasma gondii, and Cryptosporidium parvum—describing relationships between these organisms based on retained functional linkages. This comparison provided a glimpse of the highly evolved nature of P. falciparum; for instance, a deficit of nearly 26% in terms of predicted interactions is observed against P. yoelii, because of missing ortholog partners in pairs of functionally linked proteins.

A conceptual framework for integrating diverse functional genomics data was developed by reinterpreting experiments to provide numerical likelihoods that genes are functionally linked. This allows direct comparison and integration of different classes of data. The resulting probabilistic gene network estimates the functional coupling between genes. Within this framework, we reconstructed an extensive, high-quality functional gene network for Saccharomyces cerevisiae , consisting of 4681 (∼81%) of the known yeast genes linked by ∼34,000 probabilistic linkages comparable in accuracy to small-scale interaction assays. The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis.

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.

The Plasmodium Genome Database was introduced in 2000, in response to emerging needs of the malaria research community for access to genomic-scale datasets. In its earliest manifestations, prior to completion of the Plasmodium falciparum genome sequence and curated annotation, PlasmoDB focused on automated analysis of available sequence data, enabling researchers to identify draft sequences for specific genes of interest, even in the absence of the surrounding genomic context. The availability of an effectively complete P. falciparum genome sequence has stimulated a wide range of functional genomics research, and PlasmoDB has endeavored to keep pace with these studies, providing access to the underlying datasets, and allowing a variety of integrative queries, e.g., finding all genes for which both transcript and proteomics data suggest expression in gametocyte stage parasites. PlasmoDB will continue to integrate new datasets as they emerge, developing tools of interest to the malaria researcher and facilitating the discovery of new diagnostics, drugs, and vaccines. PlasmoDB provides the user with a variety of analysis tools for examining and extracting information from the genome and predicted proteome, using BLAST, electronic PCRs, defined motif searches, and tools for the analysis of microarray and proteomics data. Gene Pages provide an encyclopedic view of the Plasmodium genome, where it is possible to look up all information about a specified gene. Plasmodium parasites may be gleaned by browsing the genome in Sequence View mode, and information on specific genes may be obtained from the various Gene Pages.

Little is known about the expression of methicillin-resistant Staphylococcus aureus (MRSA) genes during infection conditions. Here, we described the transcriptome of the clinical MRSA strain USA300 derived from human cutaneous abscesses, and compared it with USA300 bacteria derived from infected kidneys in a mouse model. Remarkable similarity between the transcriptomes allowed us to identify genes encoding multiple proteases and toxins, and iron- and peptide-transporter molecules, which are upregulated in both infections and are likely important for establishment of infection. We also showed that disruption of the global transcriptional regulators agr and sae prevents in vivo upregulation of many toxins and proteases, protecting mice from lethal infection dose, and hinting at the role of these transcriptional regulators in the pathology of MRSA infection.

Background. Detailed knowledge on protein repertoire of a pathogen during host infection is needed for both developing a better understanding of the pathogenesis and defining potential therapeutic targets. Such data, however, have been missing for Staphylococcus aureus, a major human pathogen. Methods. We determined the surface proteome of methicillin-resistant S. aureus (MRSA) clone USA300 derived directly from murine systemic infection. Results. The majority of the in vivo-expressed surface-associated proteins were lipoproteins involved in nutrient acquisition, especially uptake of metal ions. Enzyme-linked immunosorbent assay (ELISA) of convalescent human serum samples revealed that proteins that were highly produced during murine experimental infection were also produced during natural human infection. We found that among the 7 highly abundant lipoproteins only MntC, which is the manganese-binding protein of the MntABC system, was essential for MRSA virulence during murine systemic infection. Moreover, we show that MntA and MntB are equally important for MRSA virulence. Conclusions. Besides providing experimental evidence that MntABC might be a potential therapeutic target for the development of antibiotics, our in vivo proteomics data will serve as a valuable basis for defining potential antigen combinations for multicomponent vaccines.

Analysis of amino acid sequences from different organisms often reveals cases in which two or more proteins encoded for separately in a genome also appear as fusions, either in the same genome or that of some other organism. Such fusion proteins, termed Rosetta stone sequences, help link disparate proteins together, and suggest the likelihood of functional interactions between the linked entities, describing local and global relationships within the proteome. These relationships help us understand the role of proteins within the context of their associations, and facilitate assignment of putative functions to uncharacterized proteins based on their linkages with proteins of known function.

Phylogenetic profiles describe the presence or absence of a protein in a set of reference genomes. Similarity between profiles is an indicator of functional coupling between gene products: the greater the similarity, the greater the likelihood of proteins sharing membership in the same pathway or cellular system. By virtue of this property, uncharacterized proteins can be assigned putative functions, based on the similarity of their profiles with those of known proteins. Profile comparisons, when extended to the entire genome, have the power to reveal functional linkages on a genome-wide scale (the functional "interactome"), elucidating both known and novel pathways and cellular systems.

Many newly identified gene products from completely sequenced genomes are difficult to characterize in the absence of sequence homology to known proteins. In such a scenario, the context of the proteins' functional associations can be used for annotation; overrepresented functional linkages with a certain class of proteins or members of a pathway allow putative function assignments based on the "guilt-by-association" principle. Two computational functional genomics methods, phylogenetic profiling and identification of Rosetta stone linkages, are described in this chapter, which allow assessment of functional linkages between proteins, consequently facilitating annotation. Phylogenetic profiling involves measuring similarity between profiles that describe the presence or absence of a protein in a set of reference genomes, whereas Rosetta stone fusion sequences help link two or more independently transcribed and translated proteins. Both methods can be applied to investigate functional associations between individual proteins, and can also be extended to reconstruct the genome-wide network of functional linkages by querying the entire protein complement of an organism.

Analysis of amino acid sequences from different organisms often reveals cases in which two or more proteins encoded for separately in a genome also appear as fusions, either in the same genome or that of some other organism. Such fusion proteins, termed Rosetta stone sequences, help link disparate proteins together, and suggest the likelihood of functional interactions between the linked entities, describing local and global relationships within the proteome. These relationships help us understand the role of proteins within the context of their associations, and facilitate assignment of putative functions to uncharacterized proteins based on their linkages with proteins of known function.

Proteins are often the ultimate expression of information encoded in the DNA (deoxyribonucleic acid). Proteins interact with other proteins, nucleic acids, and a variety of small molecules to affect cellular function. Such interactions assume the form of a vast network, portions of which are activated in a spatial and temporal manner. Understanding the makeup, properties and behaviour of this network promises to reveal many important details of the biology of organisms, ultimately helping better our knowledge of molecular and biochemical events that take place at the cellular level. Keywords: protein-protein interactions; functional interactions; protein interaction networks; protein-DNA regulation networks; transcriptional regulatory networks; COGRIM

Many newly identified gene products from completely sequenced genomes are difficult to characterize in the absence of sequence homology to known proteins. In such a scenario, the context of the proteins' functional associations can be used for annotation; overrepresented functional linkages with a certain class of proteins or members of a pathway allow putative function assignments based on the "guilt-by-association" principle. Two computational functional genomics methods, phylogenetic profiling and identification of Rosetta stone linkages, are described in this chapter, which allow assessment of functional linkages between proteins, consequently facilitating annotation. Phylogenetic profiling involves measuring similarity between profiles that describe the presence or absence of a protein in a set of reference genomes, whereas Rosetta stone fusion sequences help link two or more independently transcribed and translated proteins. Both methods can be applied to investigate functional associations between individual proteins, and can also be extended to reconstruct the genome-wide network of functional linkages by querying the entire protein complement of an organism.

We introduce a general computational method, applicable on a genome-wide scale, for the systematic discovery of uncharacterized cellular systems. Quantitative analysis of the coinheritance of pairs of genes among different organisms, calculated using phylogenetic profiles, allows the prediction of thousands of functional linkages between the corresponding proteins. A comparison of these functional linkages to known pathways reveals that calculated linkages are comparable in accuracy to genome-wide yeast two-hybrid screens or mass spectrometry interaction assays. In aggregate, these linkages describe the structure of large-scale networks, with the resulting yeast network composed of 3,875 linkages among 804 proteins, and the resulting pathogenic Escherichia coli network composed of 2,043 linkages among 828 proteins. The search of such networks for groups of uncharacterized, linked proteins led to the identification of 27 novel cellular systems from one nonpathogenic and three pathogenic bacterial genomes.

The amount of data produced by molecular biologists is growing at an exponential rate. Some of the fastest growing sets of data are measurements of gene expression, comparable in quantity only to gene sequences and the vast biological literature. Both gene expression data and sequence data offer hints as to the functions of thousands of newly discovered genes, but neither give complete answers. Therefore, much effort is being focused on integrating these large data sets and combining them with all available functional data to draw inferences about the functions of uncharacterised genes. This review discusses the most pertinent functional data for genome-wide functional inference and describes several methods by which these disparate data types are being integrated.

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In this report we describe the genomic sequence of guinea pig cytomegalovirus (GPCMV) assembled from a tissue culture-derived bacterial artificial chromosome clone, plasmid clones of viral restriction fragments, and direct PCR sequencing of viral DNA. The GPCMV genome is 232,678 bp, excluding the terminal repeats, and has a GC content of 55%. A total of 105 open reading frames (ORFs) of > 100 amino acids with sequence and/or positional homology to other CMV ORFs were annotated. Positional and sequence homologs of human cytomegalovirus open reading frames UL23 through UL122 were identified. Homology with other cytomegaloviruses was most prominent in the central ~60% of the genome, with divergence of sequence and lack of conserved homologs at the respective genomic termini. Of interest, the GPCMV genome was found in many cases to bear stronger phylogenetic similarity to primate CMVs than to rodent CMVs. The sequence of GPCMV should facilitate vaccine and pathogenesis studies in this model of congenital CMV infection.

Hepatitis C virus (HCV) infection is a major cause of liver disease and hepatocellular carcinoma. Glycan shielding has been proposed to be a mechanism by which HCV masks broadly neutralizing epitopes on its viral glycoproteins. However, the role of altered glycosylation in HCV resistance to broadly neutralizing antibodies is not fully understood. Here, we have generated potent HCV neutralizing antibodies hu5B3.v3 and MRCT10.v362 that, similar to the previously described AP33 and HCV1, bind to a highly conserved linear epitope on E2. We utilize a combination of in vitro resistance selections using the cell culture infectious HCV and structural analyses to identify mechanisms of HCV resistance to hu5B3.v3 and MRCT10.v362. Ultra deep sequencing from in vitro HCV resistance selection studies identified resistance mutations at asparagine N417 (N417S, N417T and N417G) as early as 5days post treatment. Comparison of the glycosylation status of soluble versions of the E2 glycoprotein containing the respective resistance mutations revealed a glycosylation shift from N417 to N415 in the N417S and N417T E2 proteins. The N417G E2 variant was glycosylated neither at residue 415 nor at residue 417 and remained sensitive to MRCT10.v362. Structural analyses of the E2 epitope bound to hu5B3.v3 Fab and MRCT10.v362 Fab using X-ray crystallography confirmed that residue N415 is buried within the antibody–peptide interface. Thus, in addition to previously described mutations at N415 that abrogate the β-hairpin structure of this E2 linear epitope, we identify a second escape mechanism, termed glycan shifting, that decreases the efficacy of broadly neutralizing HCV antibodies.