Bone Marrow-Derived SH-SY5Y Neuroblastoma Cells Infected with Kaposi's Sarcoma-Associated Herpesvirus Display Unique Infection Phenotypes and Growth Properties.

Kaposi's sarcoma-associated herpesvirus (KSHV) is an important oncogenic virus previously shown to be neurotropic, but studies on neuronal cell infection and pathogenesis are still very limited. Here, we characterized the effects of KSHV infection on neuronal SH-SY5Y cells by the recombinant virus rKSHV.219, which expresses both green fluorescent protein (GFP) and red fluorescent protein (RFP) to reflect the latent and lytic phases of infection. We demonstrated that infected cells have a higher growth rate and that KSHV infection can be sustained. Interestingly, the infected cells can transition spontaneously back and forth between lytic and latent phases of infection, producing progeny viruses but without any adverse effects on cell growth. In addition, transcriptome analysis of viral and cellular genes in latent and lytic cells showed that unlike other infected cell lines, the latently infected cells expressed both latent and most, but not all, of the lytic genes required for infectious virion production. The viral genes uniquely expressed by the lytic cells were mainly involved in the early steps of virus binding. Some of the cellular genes that were deregulated in both latently and lytically infected cells are involved in cell adhesion, cell signal pathways, and tumorigenesis. The downregulated cellular CCDN1, PAX5, and NFASC and upregulated CTGF, BMP4, YAP1, LEF1, and HLA-DRB1 genes were found to be associated with cell adhesion molecules (CAMs), hippo signaling, and cancer. These deregulated genes may be involved in creating an environment that is unique in neuronal cells to sustain cell growth upon KSHV infection and not observed in other infected cell types. IMPORTANCE Our study has provided evidence that neuronal SH-SY5Y cells displayed unique cellular responses upon KSHV infection. Unlike other infected cells, this neuronal cell line displayed a higher growth rate upon infection and can spontaneously transition back and forth between latent and lytic phases of infection. Unlike other latently infected cells, a number of lytic genes were also expressed in the latent phase of infection in addition to the established latent viral genes. They may play a role in deregulating a number of host genes that are involved in cell signaling and tumorigenesis in order to sustain the infection and growth advantages for the cells. Our study has provided novel insights into KSHV infection of neuronal cells and a potential new model for further studies to explore the underlying mechanism in viral and host interactions for neuronal cells and the association of KSHV with neuronal diseases.

Use of Average Mutual Information and Derived Measures to Find Coding Regions.

One of the important steps in the annotation of genomes is the identification of regions in the genome which code for proteins. One of the tools used by most annotation approaches is the use of signals extracted from genomic regions that can be used to identify whether the region is a protein coding region. Motivated by the fact that these regions are information bearing structures we propose signals based on measures motivated by the average mutual information for use in this task. We show that these signals can be used to identify coding and noncoding sequences with high accuracy. We also show that these signals are robust across species, phyla, and kingdom and can, therefore, be used in species agnostic genome annotation algorithms for identifying protein coding regions. These in turn could be used for gene identification.

Differentiation of Francisella tularensis Subspecies and Subtypes.

The highly infectious and zoonotic pathogen Francisella tularensis is the etiologic agent of tularemia, a potentially fatal disease if untreated. Despite the high average nucleotide identity, which is >99.2% for the virulent subspecies and >98% for all four subspecies, including the opportunistic microbe Francisella tularensis subsp. novicida, there are considerable differences in genetic organization. These chromosomal disparities contribute to the substantial differences in virulence observed between the various F. tularensis subspecies and subtypes. The methods currently available to genotype F. tularensis cannot conclusively identify the associated subpopulation without using time-consuming testing or complex scoring matrices. To address this need, we developed both single and multiplex quantitative real-time PCR (qPCR) assays that can accurately detect and identify the hypervirulent F. tularensis subsp. tularensis subtype A.I, the virulent F. tularensis subsp. tularensis subtype A.II, F. tularensis subsp. holarctica (also referred to as type B), and F. tularensis subsp. mediasiatica, as well as opportunistic F. tularensis subsp. novicida from each other and near neighbors, such as Francisella philomiragia, Francisella persica, and Francisella-like endosymbionts found in ticks. These fluorescence-based singleplex and non-matrix scoring multiplex qPCR assays utilize a hydrolysis probe, providing sensitive and specific F. tularensis subspecies and subtype identification in a rapid manner. Furthermore, sequencing of the amplified F. tularensis targets provides clade confirmation and informative strain-specific details. Application of these qPCR- and sequencing-based detection assays will provide an improved capability for molecular typing and clinical diagnostics, as well as facilitate the accurate identification and differentiation of F. tularensis subpopulations during epidemiological investigations of tularemia source outbreaks.

Information Theory and Cognition: A Review.

We examine how information theory has been used to study cognition over the last seven decades. After an initial burst of activity in the 1950s, the backlash that followed stopped most work in this area. The last couple of decades has seen both a revival of interest, and a more firmly grounded, experimentally justified use of information theory. We can view cognition as the process of transforming perceptions into information-where we use information in the colloquial sense of the word. This last clarification is one of the problems we run into when trying to use information theoretic principles to understand or analyze cognition. Information theory is mathematical, while cognition is a subjective phenomenon. It is relatively easy to discern a subjective connection between cognition and information; it is a different matter altogether to apply the rigor of information theory to the process of cognition. In this paper, we will look at the many ways in which people have tried to alleviate this problem. These approaches range from narrowing the focus to only quantifiable aspects of cognition or borrowing conceptual machinery from information theory to address issues of cognition. We describe applications of information theory across a range of cognition research, from neural coding to cognitive control and predictive coding.

Reclassification of Wolbachia persica as Francisella persica comb. nov. and emended description of the family Francisellaceae.

The taxonomic status of the bacterium Wolbachia persica is described, and based on the evidence presented, transfer of this species to the genus Francisella as Francisella persica comb. nov. is proposed. This reclassification is supported by data generated from genomic comparisons of W. persica ATCC VR-331T ( = FSC845T = DSM 101678T) to other near neighbours, including Francisella tularensis subsp. novicida. The full-length 16S rRNA gene sequence of strain ATCC VR-331T had 98.5 % nucleotide identity to the cognate gene in F. tularensis, with the highest similarity to subspecies novicida. Phylogenetic trees of full-length 16S rRNA gene, gyrA and recA sequences from species of the genera Wolbachia (class Alphaproteobacteria) and Francisella (class Gammaproteobacteria) indicated that W. persica ATCC VR-331T was most closely related to members of the genus Francisella and not Wolbachia. Local collinear blocks within the chromosome of strain ATCC VR-331T had considerable similarity with F. tularensis subsp. novicida, but not with any Wolbachia strain. The genomes of strain ATCC VR-331T and F. tularensis subsp. novicida Utah 112T ( = ATCC 15482T) contained an average nucleotide identity mean of 88.72 % and median of 89.18 %. Importantly, the genome of strain ATCC VR-331T contained one Francisella Pathogenicity Island, similar to F. tularensis subsp. novicida, as well as the Francisella-specific gene fopA1 and F. tularensis-specific genes fopA2 and lpnA (also referred to as tul4). In contrast to the obligate intracellular genus Wolbachia, strain ATCC VR-331T and facultative intracellular Francisella can replicate in specialized cell-free media. Collectively, these results demonstrate that Wolbachia persica should be reclassified in the genus Francisella as Francisella persica comb. nov. The type strain of Francisella persica comb. nov. is ATCC VR-331T ( = FSC845T = DSM 101678T). An emended description of the family Francisellaceae is also provided.

Metagenomic analysis of the microbial community in kefir grains.

Kefir grains as a probiotic have been subject to microbial community identification using culture-dependent and independent methods that target specific strains in the community, or that are based on limited 16S rRNA analysis. We performed whole genome shotgun pyrosequencing using two Turkish Kefir grains. Sequencing generated 3,682,455 high quality reads for a total of ∼1.6 Gbp of data assembled into 6151 contigs with a total length of ∼24 Mbp. Species identification mapped 88.16% and 93.81% of the reads rendering 4 Mpb of assembly that did not show any homology to known bacterial sequences. Identified communities in the two grains showed high concordance where Lactobacillus was the most abundant genus with a mapped abundance of 99.42% and 99.79%. This genus was dominantly represented by three species Lactobacillus kefiranofaciens, Lactobacillus buchneri and Lactobacillus helveticus with a total mapped abundance of 97.63% and 98.74%. We compared and verified our findings with 16S pyrosequencing and model based 16S data analysis. Our results suggest that microbial community profiling using whole genome shotgun data is feasible, can identify novel species data, and has the potential to generate a more accurate and detailed assessment of the underlying bacterial community, especially for low abundance species.

Identification of two small regulatory RNAs linked to virulence in Brucella abortus 2308.

Hfq is an RNA-binding protein that functions in post-transcriptional gene regulation by mediating interactions between mRNAs and small regulatory RNAs (sRNAs). Two proteins encoded by BAB1_1794 and BAB2_0612 are highly over-produced in a Brucella abortus hfq mutant compared with the parental strain, and recently, expression of orthologues of these proteins in Agrobacterium tumefaciens was shown to be regulated by two sRNAs, called AbcR1 and AbcR2. Orthologous sRNAs (likewise designated AbcR1 and AbcR2) have been identified in B. abortus 2308. In Brucella, abcR1 and abcR2 single mutants are not defective in their ability to survive in cultured murine macrophages, but an abcR1 abcR2 double mutant exhibits significant attenuation in macrophages. Additionally, the abcR1 abcR2 double mutant displays significant attenuation in a mouse model of chronic Brucella infection. Quantitative proteomics and microarray analyses revealed that the AbcR sRNAs predominantly regulate genes predicted to be involved in amino acid and polyamine transport and metabolism, and Northern blot analyses indicate that the AbcR sRNAs accelerate the degradation of the target mRNAs. In an Escherichia coli two-plasmid reporter system, overexpression of either AbcR1 or AbcR2 was sufficient for regulation of target mRNAs, indicating that the AbcR sRNAs from B. abortus 2308 perform redundant regulatory functions.

Small molecule inhibitors of Staphylococcus aureus RnpA alter cellular mRNA turnover, exhibit antimicrobial activity, and attenuate pathogenesis.

Methicillin-resistant Staphylococcus aureus is estimated to cause more U.S. deaths annually than HIV/AIDS. The emergence of hypervirulent and multidrug-resistant strains has further amplified public health concern and accentuated the need for new classes of antibiotics. RNA degradation is a required cellular process that could be exploited for novel antimicrobial drug development. However, such discovery efforts have been hindered because components of the Gram-positive RNA turnover machinery are incompletely defined. In the current study we found that the essential S. aureus protein, RnpA, catalyzes rRNA and mRNA digestion in vitro. Exploiting this activity, high through-put and secondary screening assays identified a small molecule inhibitor of RnpA-mediated in vitro RNA degradation. This agent was shown to limit cellular mRNA degradation and exhibited antimicrobial activity against predominant methicillin-resistant S. aureus (MRSA) lineages circulating throughout the U.S., vancomycin intermediate susceptible S. aureus (VISA), vancomycin resistant S. aureus (VRSA) and other Gram-positive bacterial pathogens with high RnpA amino acid conservation. We also found that this RnpA-inhibitor ameliorates disease in a systemic mouse infection model and has antimicrobial activity against biofilm-associated S. aureus. Taken together, these findings indicate that RnpA, either alone, as a component of the RNase P holoenzyme, and/or as a member of a more elaborate complex, may play a role in S. aureus RNA degradation and provide proof of principle for RNA catabolism-based antimicrobial therapy.

RAIphy: phylogenetic classification of metagenomics samples using iterative refinement of relative abundance index profiles.

BACKGROUND: Computational analysis of metagenomes requires the taxonomical assignment of the genome contigs assembled from DNA reads of environmental samples. Because of the diverse nature of microbiomes, the length of the assemblies obtained can vary between a few hundred bp to a few hundred Kbp. Current taxonomic classification algorithms provide accurate classification for long contigs or for short fragments from organisms that have close relatives with annotated genomes. These are significant limitations for metagenome analysis because of the complexity of microbiomes and the paucity of existing annotated genomes. RESULTS: We propose a robust taxonomic classification method, RAIphy, that uses a novel sequence similarity metric with iterative refinement of taxonomic models and functions effectively without these limitations. We have tested RAIphy with synthetic metagenomics data ranging between 100 bp to 50 Kbp. Within a sequence read range of 100 bp-1000 bp, the sensitivity of RAIphy ranges between 38%-81% outperforming the currently popular composition-based methods for reads in this range. Comparison with computationally more intensive sequence similarity methods shows that RAIphy performs competitively while being significantly faster. The sensitivity-specificity characteristics for relatively longer contigs were compared with the PhyloPythia and TACOA algorithms. RAIphy performs better than these algorithms at varying clade-levels. For an acid mine drainage (AMD) metagenome, RAIphy was able to taxonomically bin the sequence read set more accurately than the currently available methods, Phymm and MEGAN, and more accurately in two out of three tests than the much more computationally intensive method, PhymmBL. CONCLUSIONS: With the introduction of the relative abundance index metric and an iterative classification method, we propose a taxonomic classification algorithm that performs competitively for a large range of DNA contig lengths assembled from metagenome data. Because of its speed, simplicity, and accuracy RAIphy can be successfully used in the binning process for a broad range of metagenomic data obtained from environmental samples.

A Routine Electroencephalography Monitoring System for Automated Sports-Related Concussion Detection.

Cases of concussions in the United States keep increasing and are now up to 2 million to 3 million incidents per year. Although concussions are recoverable and usually not life-threatening, the degree and rate of recovery may vary depending on age, severity of the injury, and past concussion history. A subsequent concussion before full recovery may lead to more-severe brain damage and poorer outcomes. Electroencephalography (EEG) recordings can identify brain dysfunctionality and abnormalities, such as after a concussion. Routine EEG monitoring can be a convenient method for reducing unreported injuries and preventing long-term damage, especially among groups with a greater risk of experiencing a concussion, such as athletes participating in contact sports. Because of the relative availability of EEG compared to other brain-imaging techniques (e.g., functional magnetic resonance imaging), the use of EEG monitoring is growing for various neurological disorders. In this longitudinal study, EEG was analyzed from 4 football athletes before their athletic season and also within 7 days of concussion. Compared to a control group of 4 additional athletes, a concussion was detected with up to 99.5% accuracy using EEG recordings in the Theta-Alpha band. Classifiers that use data from only a subset of the EEG electrodes providing reliable detection are also proposed. The most effective classifiers used EEG recordings from the Central scalp region in the Beta band and over the Temporal scalp region using the Theta-Alpha band. This proof-of-concept study and preliminary findings suggest that EEG monitoring may be used to identify a sports-related concussion occurrence with a high level of accuracy and thus reduce the chance of unreported concussion.

A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences.

BACKGROUND: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. The proposed clustering algorithm uses a grammar-based distance metric to determine partitioning for a set of biological sequences. The algorithm performs clustering in which new sequences are compared with cluster-representative sequences to determine membership. If comparison fails to identify a suitable cluster, a new cluster is created. RESULTS: The performance of the proposed algorithm is validated via comparison to the popular DNA/RNA sequence clustering approach, CD-HIT-EST, and to the recently developed algorithm, UCLUST, using two different sets of 16S rDNA sequences from 2,255 genera. The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. The validation results are especially striking for large datasets. CONCLUSIONS: We introduce a fast and accurate clustering algorithm that relies on a grammar-based sequence distance. Its statistical clustering quality is validated by clustering large datasets containing 16S rDNA sequences.

Inactivation of phospholipase D diminishes Acinetobacter baumannii pathogenesis.

Acinetobacter baumannii is an emerging bacterial pathogen of considerable health care concern. Nonetheless, relatively little is known about the organism's virulence factors or their regulatory networks. Septicemia and ventilator-associated pneumonia are two of the more severe forms of A. baumannii disease. To identify virulence factors that may contribute to these disease processes, genetically diverse A. baumannii clinical isolates were evaluated for the ability to proliferate in human serum. A transposon mutant library was created in a strain background that propagated well in serum and screened for members with decreased serum growth. The results revealed that disruption of A. baumannii phospholipase D (PLD) caused a reduction in the organism's ability to thrive in serum, a deficiency in epithelial cell invasion, and diminished pathogenesis in a murine model of pneumonia. Collectively, these results suggest that PLD is an A. baumannii virulence factor.

Acinetobacter baumannii increases tolerance to antibiotics in response to monovalent cations.

Acinetobacter baumannii is well adapted to the hospital environment, where infections caused by this organism are associated with significant morbidity and mortality. Genetic determinants of antimicrobial resistance have been described extensively, yet the mechanisms by which A. baumannii regulates antibiotic resistance have not been defined. We sought to identify signals encountered within the hospital setting or human host that alter the resistance phenotype of A. baumannii. In this regard, we have identified NaCl as being an important signal that induces significant tolerance to aminoglycosides, carbapenems, quinolones, and colistin upon the culturing of A. baumannii cells in physiological NaCl concentrations. Proteomic analyses of A. baumannii culture supernatants revealed the release of outer membrane proteins in high NaCl, including two porins (CarO and a 33- to 36-kDa protein) whose loss or inactivation is associated with antibiotic resistance. To determine if NaCl affected expression at the transcriptional level, the transcriptional response to NaCl was determined by microarray analyses. These analyses highlighted 18 genes encoding putative efflux transporters that are significantly upregulated in response to NaCl. Consistent with this, the effect of NaCl on the tolerance to levofloxacin and amikacin was significantly reduced upon the treatment of A. baumannii with an efflux pump inhibitor. The effect of physiological concentrations of NaCl on colistin resistance was conserved in a panel of multidrug-resistant isolates of A. baumannii, underscoring the clinical significance of these observations. Taken together, these data demonstrate that A. baumannii sets in motion a global regulatory cascade in response to physiological NaCl concentrations, resulting in broad-spectrum tolerance to antibiotics.

Hyperthermophilic Aquifex aeolicus initiates primer synthesis on a limited set of trinucleotides comprised of cytosines and guanines.

The placement of the extreme thermophile Aquifex aeolicus in the bacterial phylogenetic tree has evoked much controversy. We investigated whether adaptations for growth at high temperatures would alter a key functional component of the replication machinery, specifically DnaG primase. Although the structure of bacterial primases is conserved, the trinucleotide initiation specificity for A. aeolicus was hypothesized to differ from other microbes as an adaptation to a geothermal milieu. To determine the full range of A. aeolicus primase activity, two oligonucleotides were designed that comprised all potential trinucleotide initiation sequences. One of the screening templates supported primer synthesis and the lengths of the resulting primers were used to predict possible initiation trinucleotides. Use of trinucleotide-specific templates demonstrated that the preferred initiation trinucleotide sequence for A. aeolicus primase was 5'-d(CCC)-3'. Two other sequences, 5'-d(GCC)-3' and d(CGC)-3', were also capable of supporting initiation, but to a much lesser degree. None of these trinucleotides were known to be recognition sequences used by other microbial primases. These results suggest that the initiation specificity of A. aeolicus primase may represent an adaptation to a thermophilic environment.

MIMOSA: Algorithms for Microbial Profiling.

A significant goal of the study of metagenomes obtained from an environment is to find the microbial diversity and the abundance of each organism in the community. Phylotyping and binning methods which address this problem generally operate using either marker sequences or by classifying each genome fragment individually. However, these approaches might not use all the information contained in the metagenome. We propose an approach based on a Multiple Input Multiple Output (MIMO) communication system model. Results from two different implementations of this approach, one using DNA-DNA hybridization simulations and one using short read mapping are evaluated using simulated and actual metagenomes and compared with other methods of phylotyping. The proposed approaches generally performed better under different scenarios including pathogen detection tasks of community complexity and low and high sequencing coverage while being highly computationally effective. The resulting framework can be integrated to metagenome analysis pipelines for phylogenetic diversity estimation. The approach is modular so that techniques other than hybridization simulations and short read mapping may be integrated. We have observed that even for low coverage samples, the method provides accurate estimates. Therefore, the use of the proposed strategy could enable the task of exploring biodiversity with limited resources.

The average mutual information profile as a genomic signature.

BACKGROUND: Occult organizational structures in DNA sequences may hold the key to understanding functional and evolutionary aspects of the DNA molecule. Such structures can also provide the means for identifying and discriminating organisms using genomic data. Species specific genomic signatures are useful in a variety of contexts such as evolutionary analysis, assembly and classification of genomic sequences from large uncultivated microbial communities and a rapid identification system in health hazard situations. RESULTS: We have analyzed genomic sequences of eukaryotic and prokaryotic chromosomes as well as various subtypes of viruses using an information theoretic framework. We confirm the existence of a species specific average mutual information (AMI) profile. We use these profiles to define a very simple, computationally efficient, alignment free, distance measure that reflects the evolutionary relationships between genomic sequences. We use this distance measure to classify chromosomes according to species of origin, to separate and cluster subtypes of the HIV-1 virus, and classify DNA fragments to species of origin. CONCLUSION: AMI profiles of DNA sequences prove to be species specific and easy to compute. The structure of AMI profiles are conserved, even in short subsequences of a species' genome, rendering a pervasive signature. This signature can be used to classify relatively short DNA fragments to species of origin.

Grammar-based distance in progressive multiple sequence alignment.

BACKGROUND: We propose a multiple sequence alignment (MSA) algorithm and compare the alignment-quality and execution-time of the proposed algorithm with that of existing algorithms. The proposed progressive alignment algorithm uses a grammar-based distance metric to determine the order in which biological sequences are to be pairwise aligned. The progressive alignment occurs via pairwise aligning new sequences with an ensemble of the sequences previously aligned. RESULTS: The performance of the proposed algorithm is validated via comparison to popular progressive multiple alignment approaches, ClustalW and T-Coffee, and to the more recently developed algorithms MAFFT, MUSCLE, Kalign, and PSAlign using the BAliBASE 3.0 database of amino acid alignment files and a set of longer sequences generated by Rose software. The proposed algorithm has successfully built multiple alignments comparable to other programs with significant improvements in running time. The results are especially striking for large datasets. CONCLUSION: We introduce a computationally efficient progressive alignment algorithm using a grammar based sequence distance particularly useful in aligning large datasets.

Lossless video sequence compression using adaptive prediction.

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

Francisella tularensis Subtype A.II Genomic Plasticity in Comparison with Subtype A.I.

Although Francisella tularensis is considered a monomorphic intracellular pathogen, molecular genotyping and virulence studies have demonstrated important differences within the tularensis subspecies (type A). To evaluate genetic variation within type A strains, sequencing and assembly of a new subtype A.II genome was achieved for comparison to other completed F. tularensis type A genomes. In contrast with the F. tularensis A.I strains (SCHU S4, FSC198, NE061598, and TI0902), substantial genomic variation was observed between the newly sequenced F. tularensis A.II strain (WY-00W4114) and the only other publically available A.II strain (WY96-3418). Genome differences between WY-00W4114 and WY96-3418 included three major chromosomal translocations, 1580 indels, and 286 nucleotide substitutions of which 159 were observed in predicted open reading frames and 127 were located in intergenic regions. The majority of WY-00W4114 nucleotide deletions occurred in intergenic regions, whereas most of the insertions and substitutions occurred in predicted genes. Of the nucleotide substitutions, 48 (30%) were synonymous and 111 (70%) were nonsynonymous. WY-00W4114 and WY96-3418 nucleotide polymorphisms were predominantly G/C to A/T allelic mutations, with WY-00W4114 having more A+T enrichment. In addition, the A.II genomes contained a considerably higher number of intact genes and longer repetitive sequences, including transposon remnants than the A.I genomes. Together these findings support the premise that F. tularensis A.II may have a fitness advantage compared to the A.I subtype due to the higher abundance of functional genes and repeated chromosomal sequences. A better understanding of the selective forces driving F. tularensis genetic diversity and plasticity is needed.

Characterization of the Acinetobacter baumannii growth phase-dependent and serum responsive transcriptomes.

Acinetobacter baumannii has emerged as a bacterial pathogen of considerable healthcare concern. Yet, little is known about the organism's basic biological processes and the regulatory networks that modulate expression of its virulence factors and antibiotic resistance. Using Affymetrix GeneChips , we comprehensively defined and compared the transcriptomes of two A. baumannii strains, ATCC 17978 and 98-37-09, during exponential and stationary phase growth in Luria-Bertani (LB) medium. Results revealed that in addition to expected growth phase-associated metabolic changes, several putative virulence factors were dramatically regulated in a growth phase-dependent manner. Because a common feature between the two most severe types of A. baumannii infection, pneumonia and septicemia, includes the organism's dissemination to visceral organs via the circulatory system, microarray studies were expanded to define the expression properties of A. baumannii during growth in human serum. Growth in serum significantly upregulated iron acquisition systems, genes associated with epithelial cell adherence and DNA uptake, as well as numerous putative drug efflux pumps. Antibiotic susceptibility testing verified that the organism exhibits increased antibiotic tolerance when cultured in human serum, as compared to LB medium. Collectively, these studies provide researchers with a comprehensive database of A. baumannii's expression properties in LB medium and serum and identify biological processes that may contribute to the organism's virulence and antibiotic resistance.