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Motivated by the development of optimal dispatching strategies for prehospital resources, we model the spatial distribution of ambulance call events in the Swedish municipality Skellefteå during 2014–2018 in order to identify important spatial covariates and discern hotspot regions. Our large-scale multivariate data point pattern of call events consists of spatial locations and marks containing the associated priority levels and sex labels. The covariates used are related to road network coverage, population density, and socio-economic status. For each marginal point pattern, we model the associated intensity function by means of a log-linear function of the covariates and their interaction terms, in combination with lasso-like elastic-net regularized composite/Poisson process likelihood estimation. This enables variable selection and collinearity adjustment as well as reduction of variance inflation from overfitting and bias from underfitting. To incorporate mobility adjustment, reflecting people’s movement patterns, we also include a nonparametric (kernel) intensity estimate as an additional covariate. The kernel intensity estimation performed here exploits a new heuristic bandwidth selection algorithm. We discover that hotspot regions occur along dense parts of the road network. A mean absolute error evaluation of the fitted model indicates that it is suitable for designing prehospital resource dispatching strategies. Supplementary materials accompanying this paper appear online.

Francisella tularensis causes the severe disease tularemia. In the present study, the aim was to identify correlates of protection in the rat co-culture model by investigating the immune responses using two vaccine candidates conferring distinct degrees of protection in rat and mouse models. The immune responses were characterized by use of splenocytes from na&iuml, ve or Live vaccine strain- (LVS) or ∆clpB/∆wbtC-immunized Fischer 344 rats as effectors and bone marrow-derived macrophages infected with the highly virulent strain SCHU S4. A complex immune response was elicited, resulting in cytokine secretion, nitric oxide production, and efficient control of the intracellular bacterial growth. Addition of LVS-immune splenocytes elicited a significantly better control of bacterial growth than ∆clpB/∆wbtC splenocytes. This mirrored the efficacy of the vaccine candidates in the rat model. Lower levels of IFN-&gamma, TNF, fractalkine, IL-2, and nitrite were present in the co-cultures with ∆clpB/∆wbtC splenocytes than in those with splenocytes from LVS-immunized rats. Nitric oxide was found to be a correlate of protection, since the levels inversely correlated to the degree of protection and inhibition of nitric oxide production completely reversed the growth inhibition of SCHU S4. Overall, the results demonstrate that the co-culture assay with rat-derived cells is a suitable model to identify correlates of protection against highly virulent strains of F. tularensis

SUMMARY Bacterial pathogens often employ RNA regulatory elements located in the 5′ untranslated regions (UTRs) to control gene expression. Using a comparative structural analysis, we examine the structure of 5′ UTRs at a global scale in the pathogenic bacterium Listeria monocytogenes under different conditions. In addition to discovering an RNA thermoswitch and detecting simultaneous interaction of ribosomes and small RNAs with mRNA, we identify structural changes in the 5′ UTR of an mRNA encoding the post-translocation chaperone PrsA2 during infection conditions. We demonstrate that the 5′ UTR of the prsA2 mRNA base pairs with the 3′ UTR of the full-length hly mRNA encoding listeriolysin O, thus preventing RNase J1-mediated degradation of the prsA2 transcript. Mutants lacking the hly-prsA2 interaction exhibit reduced virulence properties. This work highlights an additional level of RNA regulation, where the mRNA encoding a chaperone is stabilized by the mRNA encoding its substrate., In Brief By using a comparative structural analysis method targeting 5′ untranslated regions, Ignatov et al. identify different RNA-based regulatory mechanisms such as an RNA thermoswitch, a small RNA (sRNA)-mRNA interaction, and strikingly, an mRNA-mRNA interaction., Graphical Abstract

In order to optimally utilise the resources of a country’s prehospital care system, i.e. ambulance service(s),it is crucial that one is able to spatio-temporally forecast hot-spots, i.e. spatial regions and periods with anincreased risk of seeing a call to the emergency number 112 which results in the dispatch of an ambulance.Such forecasts allow the dispatcher to make strategic decisions regarding e.g. the fleet size and where todirect unoccupied ambulances. In addition, simulations based on forecasts may serve as the startingpoint for different optimal routing strategies. Although the associated data typically comes in the form ofspatio-temporal point patterns, point process based modelling attempts in the literature has been scarce.In this paper, we study a unique set of Swedish spatio-temporal ambulance call data, which consists ofthe spatial (gps) locations of the dispatch addresses and the associated days of occurrence of the calls.The spatial study region is given by the four northernmost regions of Sweden and the study period isJanuary 1, 2014 to December 31, 2018. Motivated by the non-infectious disease nature of the data, wehere employ log-Gaussian Cox processes (LGCPs) for the spatio-temporal modelling and forecasting ofthe calls. To this end, we propose a K-means based bandwidth selection method for the kernel estimationof the spatial component of the separable spatio-temporal intensity function. The temporal componentof the intensity function is modelled by means of Poisson regression, using different calendar covariates,and the spatio-temporal random field component of the random intensity of the LGCP is fitted usingsimulation via the Metropolis-adjusted Langevin algorithm. A study of the spatio-temporal dynamics ofthe data shows that a hot-spot can be found in the south eastern part of the study region, where mostpeople in the region live and our fitted model/forecasts manage to capture this behaviour quite well. Thefitted temporal component of the intensity functions reveals that there is a significant association betweenthe expected number of calls and the day of the week as well as the season of the year. In addition,non-parametric second-order spatio-temporal summary statistic estimates indicate that LGCPs seem tobe reasonable models for the data. Finally, we find that the fitted forecasts generate simulated futurespatial event patterns which quite well resemble the actual future data.

Gene co-expression networks (GCNs) can be prepared using a variety of mathematical approaches based on data sampled across diverse developmental processes, tissue types, pathologies, mutant backgrounds, and stress conditions. These networks are used to identify genes with similar expression dynamics but are prone to introducing false-positive and false-negative relationships, especially in the instance of large and heterogenous datasets. With the aim of optimizing the relevance of edges in GCNs and enhancing global biological insight, we propose a novel approach that involves a data-centering step performed simultaneously per gene and per sub-experiment, called centralization within sub-experiments (CSE). Using a gene set encoding the plant mitochondrial proteome as a case study, our results show that all CSE-based GCNs assessed had significantly more edges within the majority of the considered functional sub-networks, such as the mitochondrial electron transport chain and its complexes, than GCNs not using CSE; thus demonstrating that CSE-based GCNs are efficient at predicting canonical functions and associated pathways, here referred to as the core gene network. Furthermore, we show that correlation analyses using CSE-processed data can be used to fine-tune prediction of the function of uncharacterized genes; while its use in combination with analyses based on non-CSE data can augment conventional stress analyses with the innate connections underpinning the dynamic system being examined. Therefore, CSE is an effective alternative method to conventional batch correction approaches, particularly when dealing with large and heterogenous datasets. The method is easy to implement into a pre-existing GCN analysis pipeline and can provide enhanced biological relevance to conventional GCNs by allowing users to delineate a core gene network. Author summary Gene co-expression networks (GCNs) are the product of a variety of mathematical approaches that identify causal relationships in gene expression dynamics but are prone to the misdiagnoses of false-positives and false-negatives, especially in the instance of large and heterogenous datasets. In light of the burgeoning output of next-generation sequencing projects performed on a variety of species, and developmental or clinical conditions; the statistical power and complexity of these networks will undoubtedly increase, while their biological relevance will be fiercely challenged. Here, we propose a novel approach to generate a "core" GCN with enhanced biological relevance. Our method involves a data-centering step that effectively removes all primary treatment/tissue effects, which is simple to employ and can be easily implemented into pre-existing GCN analysis pipelines. The gain in biological relevance resulting from the adoption of this approach was assessed using a plant mitochondrial case study.

Summary: The culture negative peritonitis in Sudan 2010 was 46% exceeding 20% of the recommended ISPD (International Society for Peritoneal Dialysis) guidelines. This study reports an update after applying the standard ISPD protocol. The routine method was replaced by ISPD protocol. The culture negative rate using the ISPD guidelines dropped from 46% in the year 2010, to 39% in the year 2011, to 5% in the 2012 and to zero percent in the year 2013. Bacterial and fungal species represent (86.76%) and (13.23%) of infection and most isolates showed low resistance rate to antibiotics. Touch contamination added significantly (p = 0.0006) to the risk of contracting Peritonitis. The risk of contracting Peritonitis was 1.53 times higher in the group exposed by touch contamination. None of the other risk factors contributed significantly to Peritonitis. The study highlights the importance of implementing high hygiene practice. Keywords: Sudan, Culture negative, Peritonitis, CAPD

Bone metastasis is the lethal end‐stage of prostate cancer (PC), but the biology of bone metastases is poorly understood. The overall aim of this study was therefore to explore molecular variability in PC bone metastases of potential importance for therapy. Specifically, genome‐wide expression profiles of bone metastases from untreated patients (n = 12) and patients treated with androgen‐deprivation therapy (ADT, n = 60) were analyzed in relation to patient outcome and to morphological characteristics in metastases and paired primary tumors. Principal component analysis and unsupervised classification were used to identify sample clusters based on mRNA profiles. Clusters were characterized by gene set enrichment analysis and related to histological and clinical parameters using univariate and multivariate statistics. Selected proteins were analyzed by immunohistochemistry in metastases and matched primary tumors (n = 52) and in transurethral resected prostate (TUR‐P) tissue of a separate cohort (n = 59). Three molecular subtypes of bone metastases (MetA‐C) characterized by differences in gene expression pattern, morphology, and clinical behavior were identified. MetA (71% of the cases) showed increased expression of androgen receptor‐regulated genes, including prostate‐specific antigen (PSA), and glandular structures indicating a luminal cell phenotype. MetB (17%) showed expression profiles related to cell cycle activity and DNA damage, and a pronounced cellular atypia. MetC (12%) exhibited enriched stroma–epithelial cell interactions. MetB patients had the lowest serum PSA levels and the poorest prognosis after ADT. Combined analysis of PSA and Ki67 immunoreactivity (proliferation) in bone metastases, paired primary tumors, and TUR‐P samples was able to differentiate MetA‐like (high PSA, low Ki67) from MetB‐like (low PSA, high Ki67) tumors and demonstrate their different prognosis. In conclusion, bone metastases from PC patients are separated based on gene expression profiles into molecular subtypes with different morphology, biology, and clinical outcome. These findings deserve further exploration with the purpose of improving treatment of metastatic PC.

There are no defined correlates of protection for any intracellular pathogen, including the bacterium Francisella tularensis, which causes tularemia. Evaluating vaccine efficacy against sporadic diseases like tularemia using field trials is problematic, and therefore alternative strategies to test vaccine candidates like the Francisella Live Vaccine Strain (LVS), such as testing in animals and applying correlate measurements, are needed. Recently, we described a promising correlate strategy that predicted the degree of vaccine-induced protection in mice given parenteral challenges, primarily when using an attenuated Francisella strain. Here, we demonstrate that using peripheral blood lymphocytes (PBLs) in this approach predicts LVS-mediated protection against respiratory challenge of Fischer 344 rats with fully virulent F. tularensis, with exceptional sensitivity and specificity. Rats were vaccinated with a panel of LVS-derived vaccines and subsequently given lethal respiratory challenges with Type A F. tularensis. In parallel, PBLs from vaccinated rats were evaluated for their functional ability to control intramacrophage Francisella growth in in vitro co-culture assays. PBLs recovered from co-cultures were also evaluated for relative gene expression using a large panel of genes identified in murine studies. In vitro control of LVS intramacrophage replication reflected the hierarchy of protection. Further, despite variability between individuals, 22 genes were significantly more up-regulated in PBLs from rats vaccinated with LVS compared to those from rats vaccinated with the variant LVS-R or heat killed LVS, which were poorly protective. These genes included IFN-gamma, IL-21, NOS2, LTA, T-bet, IL-12rβ2, and CCL5. Most importantly, combining quantifications of intramacrophage growth control with 5-7 gene expression levels using multivariate analyses discriminated protected from non-protected individuals with greater than 95% sensitivity and specificity. The results therefore support translation of this approach to non-human primates and people to evaluate new vaccines against Francisella and other intracellular pathogens.

Geographic distribution of cases was correlated with the locations of lakes and rivers., The zoonotic disease tularemia is endemic in large areas of the Northern Hemisphere, but research is lacking on patterns of spatial distribution and connections with ecologic factors. To describe the spatial epidemiology of and identify ecologic risk factors for tularemia incidence in Sweden, we analyzed surveillance data collected over 29 years (1984–2012). A total of 4,830 cases were notified, of which 3,524 met all study inclusion criteria. From the first to the second half of the study period, mean incidence increased 10-fold, from 0.26/100,000 persons during 1984–1998 to 2.47/100,000 persons during 1999–2012 (p

Urinary tract infections (UTIs) are among the most common bacterial infections in men and urine culture is gold standard for diagnosis. Considering the high prevalence of culture-negative specimens, any method that identifies such specimens is of interest. The aim was to evaluate a new screening concept for flow cytometry analysis (FCA). The outcomes were evaluated against urine culture, uropathogen species and three conventional screening methods. A prospective, consecutive study examined 1,312 urine specimens, collected during January and February 2012. The specimens were analyzed using the Sysmex UF1000i FCA. Based on the FCA data culture negative specimens were identified in a new model by use of linear discriminant analysis (FCA-LDA). In total 1,312 patients were included. In- and outpatients represented 19.6% and 79.4%, respectively; 68.3% of the specimens originated from women. Of the 610 culture-positive specimens, Escherichia coli represented 64%, enterococci 8% and Klebsiella spp. 7%. Screening with FCA-LDA at 95% sensitivity identified 42% (552/1312) as culture negative specimens when UTI was defined according to European guidelines. The proposed screening method was either superior or similar in comparison to the three conventional screening methods. In conclusion, the proposed/suggested and new FCA-LDA screening method was superior or similar to three conventional screening methods. We recommend the proposed screening method to be used in clinic to exclude culture negative specimens, to reduce workload, costs and the turnaround time. In addition, the FCA data may add information that enhance handling and support diagnosis of patients with suspected UTI pending urine culture. Errata European Journal of Clinical Microbiology & Infectious Diseases (2017) 36: 1705. https://doi.org/10.1007/s10096-017-3059-8

Autosomal recessive osteopetrosis (ARO) is a heterogeneous disorder, characterized by defective osteoclastic resorption of bone that results in increased bone density. We have studied nine individuals with an intermediate form of ARO, from the county of Västerbotten in Northern Sweden. All afflicted individuals had an onset in early infancy with optic atrophy, and in four patients anemia was present at diagnosis. Tonsillar herniation, foramen magnum stenosis, and severe osteomyelitis of the jaw were common clinical features. Whole exome sequencing, verified by Sanger sequencing, identified a splice site mutation c.212 + 1 G > T in the SNX10 gene encoding sorting nexin 10. Sequence analysis of the SNX10 transcript in patients revealed activation of a cryptic splice site in intron 4 resulting in a frame shift and a premature stop (p.S66Nfs * 15). Haplotype analysis showed that all cases originated from a single mutational event, and the age of the mutation was estimated to be approximately 950 years. Functional analysis of osteoclast progenitors isolated from peripheral blood of patients revealed that stimulation with receptor activator of nuclear factor kappa-B ligand (RANKL) resulted in a robust formation of large, multinucleated osteoclasts which generated sealing zones; however these osteoclasts exhibited defective ruffled borders and were unable to resorb bone in vitro.

PURPOSE: Clinical test batteries for evaluation of knee function after injury to the Anterior Cruciate Ligament (ACL) should be valid and feasible, while reliably capturing the outcome of rehabilitation. There is currently a lack of consensus as to which of the many available assessment tools for knee function that should be included. The present aim was to use a statistical approach to investigate the contribution of frequently used tests to avoid redundancy, and filter them down to a proposed comprehensive and yet feasible test battery for long-term evaluation after ACL injury. METHODS: In total 48 outcome variables related to knee function, all potentially relevant for a long-term follow-up, were included from a cross-sectional study where 70 ACL-injured (17-28 years post injury) individuals were compared to 33 controls. Cluster analysis and logistic regression were used to group variables and identify an optimal test battery, from which a summarized estimator of knee function representing various functional aspects was derived. RESULTS: As expected, several variables were strongly correlated, and the variables also fell into logical clusters with higher within-correlation (max ρ = 0.61) than between clusters (max ρ = 0.19). An extracted test battery with just four variables assessing one-leg balance, isokinetic knee extension strength and hop performance (one-leg hop, side hop) were mathematically combined to an estimator of knee function, which acceptably classified ACL-injured individuals and controls. This estimator, derived from objective measures, correlated significantly with self-reported function, e.g. Lysholm score (ρ = 0.66; p

SUMMARYSweden reports large and variable numbers of human tularemia cases, but the high-risk regions are anecdotally defined and factors explaining annual variations are poorly understood. Here, high-risk regions were identified by spatial cluster analysis on disease surveillance data for 1984–2012. Negative binomial regression with five previously validated predictors (including predicted mosquito abundance and predictors based on local weather data) was used to model the annual number of tularemia cases within the high-risk regions. Seven high-risk regions were identified with annual incidences of 3·8–44 cases/100 000 inhabitants, accounting for 56·4% of the tularemia cases but only 9·3% of Sweden's population. For all high-risk regions, most cases occurred between July and September. The regression models explained the annual variation of tularemia cases within most high-risk regions and discriminated between years with and without outbreaks. In conclusion, tularemia in Sweden is concentrated in a few high-risk regions and shows high annual and seasonal variations. We present reproducible methods for identifying tularemia high-risk regions and modelling tularemia cases within these regions. The results may help health authorities to target populations at risk and lay the foundation for developing an early warning system for outbreaks.

Currently, there are no licensed vaccines and no correlates of protection against Francisella tularensis, which causes tularemia. We recently demonstrated that measuring in vitro control of intramacrophage bacterial growth by murine F. tularensis-immune splenocytes, as well as transcriptional analyses, discriminated Francisella vaccines of different efficacies. Further, we identified potential correlates of protection against systemic challenge. Here, we extended this approach by studying leukocytes derived from lungs and livers of mice immunized by parenteral and respiratory routes with F. tularensis vaccines. Liver and lung leukocytes derived from intradermally and intranasally vaccinated mice controlled in vitro Francisella Live Vaccine Strain (LVS) intramacrophage replication in patterns similar to those of splenocytes. Gene expression analyses of potential correlates also revealed similar patterns in liver cells and splenocytes. In some cases (e.g., tumor necrosis factor alpha [TNF-α], interleukin 22 [IL-22], and granulocyte-macrophage colony-stimulating factor [GM-CSF]), liver cells exhibited even higher relative gene expression, whereas fewer genes exhibited differential expression in lung cells. In contrast with their strong ability to control LVS replication, splenocytes from intranasally vaccinated mice expressed few genes with a hierarchy of expression similar to that of splenocytes from intradermally vaccinated mice. Thus, the relative levels of gene expression vary between cell types from different organs and by vaccination route. Most importantly, because studies comparing cell sources and routes of vaccination supported the predictive validity of this coculture and gene quantification approach, we combined in vitro LVS replication with gene expression data to develop analytical models that discriminated between vaccine groups and successfully predicted the degree of vaccine efficacy. Thus, this strategy remains a promising means of identifying and quantifying correlative T cell responses., IMPORTANCE Identifying and quantifying correlates of protection is especially challenging for intracellular bacteria, including Francisella tularensis. F. tularensis is classified as a category A bioterrorism agent, and no vaccines have been licensed in the United States, but tularemia is a rare disease. Therefore, clinical trials to test promising vaccines are impractical. In this report, we further evaluated a novel approach to developing correlates by assessing T cell immune responses in lungs and livers of differentially vaccinated mice; these nonprofessional immune tissues are colonized by Francisella. The relative degree of vaccine efficacy against systemic challenge was reflected by the ability of immune T cells, particularly liver T cells, to control the intramacrophage replication of bacteria in vitro and by relative gene expression of several immunological mediators. We therefore developed analytical models that combined bacterial replication data and gene expression data. Several resulting models provided excellent discrimination between vaccines of different efficacies.

The yeast Mediator complex can be divided into three modules, designated Head, Middle and Tail. Tail comprises the Med2, Med3, Med5, Med15 and Med16 protein subunits, which are all encoded by genes that are individually non-essential for viability. In cells lacking Med16, Tail is displaced from Head and Middle. However, inactivation of MED5/MED15 and MED15/MED16 are synthetically lethal, indicating that Tail performs essential functions as a separate complex even when it is not bound to Middle and Head. We have used the N-Degron method to create temperature-sensitive (ts) mutants in the Mediator tail subunits Med5, Med15 and Med16 to study the immediate effects on global gene expression when each subunit is individually inactivated, and when Med5/15 or Med15/16 are inactivated together. We identify 25 genes in each double mutant that show a significant change in expression when compared to the corresponding single mutants and to the wild type strain. Importantly, 13 of the 25 identified genes are common for both double mutants. We also find that all strains in which MED15 is inactivated show down-regulation of genes that have been identified as targets for the Ace2 transcriptional activator protein, which is important for progression through the G1 phase of the cell cycle. Supporting this observation, we demonstrate that loss of Med15 leads to a G1 arrest phenotype. Collectively, these findings provide insight into the function of the Mediator Tail module.

Males and females share most of their genomes, and differences between the sexes can therefore not evolve through sequence divergence in protein coding genes. Sexual dimorphism is instead restricted to occur through sex-specific expression and splicing of gene products. Evolution of sexual dimorphism through these mechanisms should, however, also be constrained when the sexes share the genetic architecture for regulation of gene expression. Despite these obstacles, sexual dimorphism is prevalent in the animal kingdom and commonly evolves rapidly. Here, we ask whether the genetic architecture of gene expression is plastic and easily molded by sex-specific selection, or if sexual dimorphism evolves rapidly despite pervasive genetic constraint. To address this question, we explore the relationship between the intersexual genetic correlation for gene expression (rMF), which captures how independently genes are regulated in the sexes, and the evolution of sex-biased gene expression. Using transcriptome data from Drosophila melanogaster, we find that most genes have a high rMF and that genes currently exposed to sexually antagonistic selection have a higher average rMF than other genes. We further show that genes with a high rMF have less pronounced sex-biased gene expression than genes with a low rMF within D. melanogaster and that the strength of the rMF in D. melanogaster predicts the degree to which the sex bias of a gene's expression has changed between D. melanogaster and six other species in the Drosophila genus. In sum, our results show that a shared genome constrains both short- and long-term evolution of sexual dimorphism.

Patient outcome from glioma may be influenced by germline variation. Considering the importance of DNA repair in cancer biology as well as in response to treatment, we studied the relationship between 1458 SNPs, which captured the majority of the common genetic variation in 136 DNA repair genes, in 138 glioblastoma samples from Sweden and Denmark. We confirmed our findings in an independent cohort of 121 glioblastoma patients from the UK. Our analysis revealed nine SNPs annotating MSH2, RAD51L1 and RECQL4 that were significantly (p < 0.05) associated with glioblastoma survival.

The Pr promoter is the first verified member of a class of bacterial σ(70)-promoters that only possess a single match to consensus within its -10 element. In its native context, the activity of this promoter determines the ability of Pseudomonas putida CF600 to degrade phenolic compounds, which provides proof-of-principle for the significance of such promoters. Lack of identity within the -10 element leads to non-detection of Pr-like promoters by current search engines, because of their bias for detection of the -10 motif. Here, we report a mutagenesis analysis of Pr that reveals strict sequence requirements for its activity that includes an essential -15 element and preservation of non-consensus bases within its -35 and -10 elements. We found that highly similar promoters control plasmid- and chromosomally- encoded phenol degradative systems in various Pseudomonads. However, using a purpose-designed promoter-search algorithm and activity analysis of potential candidate promoters, no bona fide Pr-like promoter could be found in the entire genome of P. putida KT2440. Hence, Pr-like σ(70)-promoters, which have the potential to be a widely distributed class of previously unrecognized promoters, are in fact highly restricted and remain in a class of their own.

Background Machine learning is a powerful approach for describing and predicting classes in microarray data. Although several comparative studies have investigated the relative performance of various machine learning methods, these often do not account for the fact that performance (e.g. error rate) is a result of a series of analysis steps of which the most important are data normalization, gene selection and machine learning. Results In this study, we used seven previously published cancer-related microarray data sets to compare the effects on classification performance of five normalization methods, three gene selection methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly employing a double cross validation approach. Since performance varies greatly between data sets, we devised an analysis method that first compares methods within individual data sets and then visualizes the comparisons across data sets. We discovered both well performing individual methods and synergies between different methods. Conclusion Support Vector Machines with a radial basis kernel, linear kernel or polynomial kernel of degree 2 all performed consistently well across data sets. We show that there is a synergistic relationship between these methods and gene selection based on the T-test and the selection of a relatively high number of genes. Also, we find that these methods benefit significantly from using normalized data, although it is hard to draw general conclusions about the relative performance of different normalization procedures.

Elongator complex is required for formation of the side chains at position 5 of modified nucleosides 5-carbamoylmethyluridine (ncm5U34), 5-methoxycarbonylmethyluridine (mcm5U34), and 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U34) at wobble position in tRNA. These modified nucleosides are important for efficient decoding during translation. In a recent publication, Elongator complex was implicated to participate in telomeric gene silencing and DNA damage response by interacting with proliferating cell nuclear antigen (PCNA). Here we show that elevated levels of tRNALys s2 UUU, tRNAGln s2 UUG, and tRNAGlu s2 UUC, which in a wild-type background contain the mcm5s2U nucleoside at position 34, suppress the defects in telomeric gene silencing and DNA damage response observed in the Elongator mutants. We also found that the reported differences in telomeric gene silencing and DNA damage response of various elp3 alleles correlated with the levels of modified nucleosides at U34. Defects in telomeric gene silencing and DNA damage response are also observed in strains with the tuc2Δ mutation, which abolish the formation of the 2-thio group of the mcm5s2U nucleoside in tRNALys mcm5s2UUU, tRNAGln mcm5s2UUG, and tRNAGlu mcm5s2UUC. These observations show that Elongator complex does not directly participate in telomeric gene silencing and DNA damage response, but rather that modified nucleosides at U34 are important for efficient expression of gene products involved in these processes. Consistent with this notion, we found that expression of Sir4, a silent information regulator required for assembly of silent chromatin at telomeres, was decreased in the elp3Δ mutants., Author Summary Elongator is a conserved protein complex in eukaryotes. Studies in yeast, worms, and plants have revealed that Elongator complex is required for formation of mcm5 and ncm5 side chains at wobble uridines in a subset of tRNA species. The primary function of Elongator complex in yeast is to modify U34 in tRNAs. Lack of these tRNA modifications causes pleiotropic phenotypes in yeast Elongator mutants due to inefficient translation. In this report, we demonstrate that the defects in telomeric silencing and DNA damage response observed in yeast Elongator mutants are a consequence of a tRNA modification defect. We suggest that the requirement of Elongator complex in tRNA modification is conserved in all eukaryotes, and diseases linked to human Elongator mutations may involve impaired translation due to lack of tRNA modifications.

Background Francisella tularensis is a facultative intracellular bacterial pathogen and the etiological agent of tularemia. The subspecies F. tularensis tularensis is especially virulent for humans when inhaled and respiratory tularemia is associated with high mortality if not promptly treated. A live vaccine strain (LVS) derived from the less virulent holarctica subspecies confers incomplete protection against aerosol challenge with subsp. tularensis. Moreover, correlates of protection have not been established for LVS. Methodology/Principal Findings In the present study we compare molecular immune responses elicited by LVS and two defined deletion mutants of clinical subsp. tularensis strain, SCHU S4, that confer enhanced protection in a mouse model. BALB/c mice were immunized intradermally then challenged with an aerosol of SCHU S4 six weeks later. Changes in the levels of a selected panel of cytokines and chemokines were examined in the lungs, spleens, and sera of vaccinated and challenged mice. Mostly, increased cytokine and chemokine levels correlated with increased bacterial burden. However, after adjusting for this variable, immunization with either of the two Schu S4 mutants resulted in higher levels of several pulmonary cytokines, versus those resulting after LVS immunization, including IL-17. Moreover, treatment of mice immunized with ΔclpB with anti-IL-17 antibodies post-challenge enhanced lung infection. Conclusions/Significance This is the first report characterizing local and systemic cytokine and chemokine responses in mice immunized with vaccines with different efficacies against aerosol challenge with virulent F. tularensis subsp. tularensis. It shows that increases in the levels of most of these immunomodulators, including those known to be critical for protective immunity, do not superficially correlate with protection unless adjusted for the effects of bacterial burden. Additionally, several cytokines were selectively suppressed in the lungs of naïve mice, suggesting that one mechanism of vaccine action is to overcome this pathogen-induced immunosuppression.

Background The homeodomain transcription factor IPF1/PDX1 exerts a dual role in the pancreas; Ipf1/Pdx1 global null mutants fail to develop a pancreas whereas conditional inactivation of Ipf1/Pdx1 in β-cells leads to impaired β-cell function and diabetes. Although several putative target genes have been linked to the β-cell function of Ipf1/Pdx1, relatively little is known with respect to genes regulated by IPF1/PDX1 in early pancreatic progenitor cells. Results Microarray analyses identified a total of 111 genes that were differentially expressed in e10.5 pancreatic buds of Ipf1/Pdx1 -/- embryos. The expression of one of these, Spondin 1, which encodes an extracellular matrix protein, has not previously been described in the pancreas. Quantitative real-time RT-PCR analyses and immunohistochemical analyses also revealed that the expression of FgfR2IIIb, that encodes the receptor for FGF10, was down-regulated in Ipf1/Pdx1 -/- pancreatic progenitor cells. Conclusion This microarray analysis has identified a number of candidate genes that are differentially expressed in Ipf1/Pdx1 -/- pancreatic buds. Several of the differentially expressed genes were known to be important for pancreatic progenitor cell proliferation and differentiation whereas others have not previously been associated with pancreatic development.

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data.