Impact of Anti-Mycotic Drugs on the Osteogenic Response of Bone Marrow Mesenchymal Stem Cells In Vitro

The treatment of fungal bone infections and infected non-unions is a huge challenge in modern trauma and orthopedics, which normally contain the local and systemic administration of anti-fungal drugs. Although frequently used, little is known about the impact of systemic and locally administered fungicides on the osteogenic regenerative capabilities of infected bone tissue, especially upon the osteogenesis of human bone marrow mesenchymal stem cells (BM-hMSCs). This study evaluates the effects of the three most common fungicides for the systemic treatment of bone infections, Voriconazole (VOR), liposomal Amphotericin B (LAMB), and Fluconazole (FLU), as well as the effects of VOR and LAMB-loaded Polymethylmethacrylate (PMMA) cement chips in different concentrations upon the osteogenic response of BM-hMSCs in vitro. Within this study, we compared the ability of BM-hMSC to differentiate into osteoblast-like cells and synthesize hydroxyapatite as assessed by radioactive 99mTechnetium-Hydroxydiphosphonate (99mTc-HDP) labeling, cell proliferation, and analyses of supernatants upon various osteogenic parameters. Our results revealed that VOR added to the cell culture medium affects the osteogenic potential of BM-hMSC negatively, while there were no detectable effects of LAMB and FLU. Moreover, we showed dose-dependent negative effects of high- and extended-dose fungicide-loaded PMMA cement due to cytotoxicity, with a higher cytotoxic potential of VOR than LAMB, while low-dose fungicide-loaded PMMA had no significant effect on the osteogenic potential of BM-hMSC in vitro.

Impact of Antibiotic-Loaded PMMA Spacers on the Osteogenic Potential of hMSCs

Antibiotic-loaded PMMA bone cement is frequently used in modern trauma and orthopedic surgery. Although many of the antibiotics routinely applied are described to have cytotoxic effects in the literature, clinical experience shows no adverse effects for bone healing. To determine the effects of antibiotic-loaded PMMA spacers on osteogenesis in vitro, we cultivated human bone marrow mesenchymal stem cells (BM-hMSCs) in the presence of PMMA spacers containing Gentamicin, Vancomycin, Gentamicin + Clindamycin as well as Gentamicin + Vancomycin in addition to a blank control (agarose) and PMMA containing no antibiotics. The cell number was assessed with DAPI staining, and the osteogenic potential was evaluated by directly measuring the amount of hydroxyapatite synthesized using radioactive 99mTc-HDP labelling as well as measuring the concentration of calcium and phosphate in the cell culture medium supernatant. The results showed that Gentamicin and Vancomycin as well as their combination show a certain amount of cytotoxicity but no negative effect on osteogenic potential. The combination of Gentamicin and Clindamycin, on the other hand, led to a drastic reduction in both the cell count and the osteogenic potential.

Fear circuit-based neurobehavioral signatures mirror resilience to chronic social stress in mouse

Consistent evidence from human data points to successful threat-safety discrimination and responsiveness to extinction of fear memories as key characteristics of resilient individuals. To promote valid cross-species approaches for the identification of resilience mechanisms, we establish a translationally informed mouse model enabling the stratification of mice into three phenotypic subgroups following chronic social defeat stress, based on their individual ability for threat-safety discrimination and conditioned learning: the Discriminating-avoiders, characterized by successful social threat-safety discrimination and extinction of social aversive memories; the Indiscriminate-avoiders, showing aversive response generalization and resistance to extinction, in line with findings on susceptible individuals; and the Non-avoiders displaying impaired aversive conditioned learning. To explore the neurobiological mechanisms underlying the stratification, we perform transcriptome analysis within three key target regions of the fear circuitry. We identify subgroup-specific differentially expressed genes and gene networks underlying the behavioral phenotypes, i.e., the individual ability to show threat-safety discrimination and respond to extinction training. Our approach provides a translationally informed template with which to characterize the behavioral, molecular, and circuit bases of resilience in mice.

Enabling technologies towards personalization of scaffolds for large bone defect regeneration

Additive manufacturing (AM) can deliver personalized scaffolds to support large volume defect tissue regeneration - a major clinical challenge in many medical disciplines. The freedom in scaffold design and composition (biomaterials and biologics) offered by AM yields a plethora of possibilities but is confronted with a heterogenous biological regeneration potential across individuals. A key challenge is to make the right choice for individualized scaffolds that match biology, anatomy, and mechanics of patients. This review provides an overview of state-of-the-art technologies, that is, in silico modelling for scaffold design, omics and bioinformatics to capture patient biology and information technology for data management, that, when combined in a synergistic way with AM, have great potential to make personalized tissue regeneration strategies available to all patients, empowering precision medicine.

Motor neuron translatome reveals deregulation of SYNGR4 and PLEKHB1 in mutant TDP-43 amyotrophic lateral sclerosis models

Amyotrophic lateral sclerosis (ALS) is an incurable neurological disease with progressive loss of motor neuron (MN) function in the brain and spinal cord. Mutations in TARDBP, encoding the RNA-binding protein TDP-43, are one cause of ALS, and TDP-43 mislocalization in MNs is a key pathological feature of >95% of ALS cases. While numerous studies support altered RNA regulation by TDP-43 as a major cause of disease, specific changes within MNs that trigger disease onset remain unclear. Here, we combined translating ribosome affinity purification (TRAP) with RNA sequencing to identify molecular changes in spinal MNs of TDP-43–driven ALS at motor symptom onset. By comparing the MN translatome of hTDP-43^A315T mice to littermate controls and to mice expressing wild type hTDP-43, we identified hundreds of mRNAs that were selectively up- or downregulated in MNs. We validated the deregulated candidates Tex26, Syngr4, and Plekhb1 mRNAs in an independent TRAP experiment. Moreover, by quantitative immunostaining of spinal cord MNs, we found corresponding protein level changes for SYNGR4 and PLEKHB1. We also observed these changes in spinal MNs of an independent ALS mouse model caused by a different patient mutant allele of TDP-43, suggesting that they are general features of TDP-43-driven ALS. Thus, we identified SYNGR4 and PLEKHB1 to be deregulated in MNs at motor symptom onset in TDP-43-driven ALS models. This spatial and temporal pattern suggests that these proteins could be functionally important for driving the transition to the symptomatic phase of the disease.

DNA Methyltransferase 1 (DNMT1) Function Is Implicated in the Age-Related Loss of Cortical Interneurons

Increased life expectancy in modern society comes at the cost of age-associated disabilities and diseases. Aged brains not only show reduced excitability and plasticity, but also a decline in inhibition. Age-associated defects in inhibitory circuits likely contribute to cognitive decline and age-related disorders. Molecular mechanisms that exert epigenetic control of gene expression contribute to age-associated neuronal impairments. Both DNA methylation, mediated by DNA methyltransferases (DNMTs), and histone modifications maintain neuronal function throughout lifespan. Here we provide evidence that DNMT1 function is implicated in the age-related loss of cortical inhibitory interneurons. Dnmt1 deletion in parvalbumin-positive interneurons attenuates their age-related decline in the cerebral cortex. Moreover, conditional Dnmt1-deficient mice show improved somatomotor performance and reduced aging-associated transcriptional changes. A decline in the proteostasis network, responsible for the proper degradation and removal of defective proteins, is implicated in age- and disease-related neurodegeneration. Our data suggest that DNMT1 acts indirectly on interneuron survival in aged mice by modulating the proteostasis network during life-time.

DNA Methylation-Mediated Modulation of Endocytosis as Potential Mechanism for Synaptic Function Regulation in Murine Inhibitory Cortical Interneurons

The balance of excitation and inhibition is essential for cortical information processing, relying on the tight orchestration of the underlying subcellular processes. Dynamic transcriptional control by DNA methylation, catalyzed by DNA methyltransferases (DNMTs), and DNA demethylation, achieved by ten–eleven translocation (TET)-dependent mechanisms, is proposed to regulate synaptic function in the adult brain with implications for learning and memory. However, focus so far is laid on excitatory neurons. Given the crucial role of inhibitory cortical interneurons in cortical information processing and in disease, deciphering the cellular and molecular mechanisms of GABAergic transmission is fundamental. The emerging relevance of DNMT and TET-mediated functions for synaptic regulation irrevocably raises the question for the targeted subcellular processes and mechanisms. In this study, we analyzed the role dynamic DNA methylation has in regulating cortical interneuron function. We found that DNMT1 and TET1/TET3 contrarily modulate clathrin-mediated endocytosis. Moreover, we provide evidence that DNMT1 influences synaptic vesicle replenishment and GABAergic transmission, presumably through the DNA methylation-dependent transcriptional control over endocytosis-related genes. The relevance of our findings is supported by human brain sample analysis, pointing to a potential implication of DNA methylation-dependent endocytosis regulation in the pathophysiology of temporal lobe epilepsy, a disease characterized by disturbed synaptic transmission.

The secreted BMP antagonist ERFE is required for the development of a functional circulatory system in Xenopus

The hormone Erythroferrone (ERFE) is a member of the C1q/TNF-related protein family that regulates iron homeostasis through the suppression of hamp. In a gain of function screen in Xenopus embryos, we identified ERFE as a potent secondary axis-inducing agent. Experiments in Xenopus embryos and ectodermal explants revealed that ERFE functions as a selective inhibitor of the BMP pathway and the conserved C1q domain is not required for this activity. Inhibition occurs at the extracelluar level, through the interaction of ERFE with the BMP ligand. During early Xenopus embryogenesis, erfe is first expressed in the ventral blood islands where initial erythropoiesis occurs and later in circulating blood cells. ERFE knockdown does not alter the expression of etv.2, aplnr and flt1 in tailbud stage embryos indicating endothelial cell specification is independent of ERFE. However, in tadpole embryos, defects of the vascular network and primitive blood circulation are observed as well as edema formation. RNAseq analysis of ERFE morphant embryos also revealed the inhibition of gja4 indicating disruption of dorsal aorta formation.

Nuclear Pre-snRNA Export Is an Essential Quality Assurance Mechanism for Functional Spliceosomes

Removal of introns from pre-mRNAs is an essential step in eukaryotic gene expression, mediated by spliceosomes that contain snRNAs as key components. Although snRNAs are transcribed in the nucleus and function in the same compartment, all except U6 shuttle to the cytoplasm. Surprisingly, the physiological relevance for shuttling is unclear, in particular because the snRNAs in Saccharomyces cerevisiae were reported to remain nuclear. Here, we show that all yeast pre-snRNAs including U6 undergo a stepwise maturation process after nuclear export by Mex67 and Xpo1. Sm- and Lsm-ring attachment occurs in the cytoplasm and is important for the snRNA re-import, mediated by Cse1 and Mtr10. Finally, nuclear pre-snRNA cleavage and trimethylation of the 5'-cap finalizes shuttling. Importantly, preventing pre-snRNAs from being exported or processed results in faulty spliceosome assembly and subsequent genome-wide splicing defects. Thus, pre-snRNA export is obligatory for functional splicing and resembles an essential evolutionarily conserved quality assurance step.

Expression of the DNA-Binding Factor TOX Promotes the Encephalitogenic Potential of Microbe-Induced Autoreactive CD8+ T Cells

Infections are thought to trigger CD8⁺ cytotoxic T lymphocyte (CTL) responses during autoimmunity. However, the transcriptional programs governing the tissue-destructive potential of CTLs remain poorly defined. In a model of central nervous system (CNS) inflammation, we found that infection with lymphocytic choriomeningitis virus (LCMV), but not Listeria monocytogenes (Lm), drove autoimmunity. The DNA-binding factor TOX was induced in CTLs during LCMV infection and was essential for their encephalitogenic properties, and its expression was inhibited by interleukin-12 during Lm infection. TOX repressed the activity of several transcription factors (including Id2, TCF-1, and Notch) that are known to drive CTL differentiation. TOX also reduced immune checkpoint sensitivity by restraining the expression of the inhibitory checkpoint receptor CD244 on the surface of CTLs, leading to increased CTL-mediated damage in the CNS. Our results identify TOX as a transcriptional regulator of tissue-destructive CTLs in autoimmunity, offering a potential mechanistic link to microbial triggers.

The IL-1 Pathway Is Hyperactive in Hidradenitis Suppurativa and Contributes to Skin Infiltration and Destruction

Hidradenitis suppurativa (HS) (also designated acne inversa) is a chronic inflammatory disease characterized by painful purulent skin lesions and progressive destruction of skin architecture. Despite the high burden for the patients, pathogenetic pathways underlying HS alterations remain obscure. When we examined the HS cytokine pattern, IL-1β turned out to be a highly prominent cytokine, overexpressed even compared with psoriatic lesions. Analyses of IL-1β-induced transcriptome in various cell types showed overlapping profiles, with upregulations of molecules causing immune cell infiltration and extracellular matrix degradation, and of specific cytokines including IL-6, IL-32, and IL-36. Matching cellular IL-1 receptor levels, dermal fibroblasts showed both the strongest and broadest IL-1β response, which was not clearly shared or strengthened by other cytokines. The IL-1β signature was specifically present in HS lesions and could be reversed by application of IL-1 receptor antagonist. Search for blood parameters associated with IL-1β pathway activity in HS identified serum amyloid A, which was synergistically induced by IL-1β and IL-6 in hepatocytes. Consequently, strongly elevated blood serum amyloid A levels in HS correlated positively with the extent of inflammatory skin alterations. In summary, the IL-1β pathway represents a pathogenetic cascade, whose activity may be therapeutically targeted and monitored by blood SAA levels.

Functional equivalence of germ plasm organizers

The proteins Oskar (Osk) in Drosophila and Bucky ball (Buc) in zebrafish act as germ plasm organizers. Both proteins recapitulate germ plasm activities but seem to be unique to their animal groups. Here, we discover that Osk and Buc show similar activities during germ cell specification. Drosophila Osk induces additional PGCs in zebrafish. Surprisingly, Osk and Buc do not show homologous protein motifs that would explain their related function. Nonetheless, we detect that both proteins contain stretches of intrinsically disordered regions (IDRs), which seem to be involved in protein aggregation. IDRs are known to rapidly change their sequence during evolution, which might obscure biochemical interaction motifs. Indeed, we show that Buc binds to the known Oskar interactors Vasa protein and nanos mRNA indicating conserved biochemical activities. These data provide a molecular framework for two proteins with unrelated sequence but with equivalent function to assemble a conserved core-complex nucleating germ plasm.

Multicellular organisms use gametes for their propagation. Gametes are formed from germ cells, which are specified during embryogenesis in some animals by the inheritance of RNP granules known as germ plasm. Transplantation of germ plasm induces extra germ cells, whereas germ plasm ablation leads to the loss of gametes and sterility. Therefore, germ plasm is key for germ cell formation and reproduction. However, the molecular mechanisms of germ cell specification by germ plasm in the vertebrate embryo remain an unsolved question. Proteins, which assemble the germ plasm, are known as germ plasm organizers. Here, we show that the two germ plasm organizers Oskar from the fly and Bucky ball from the fish show similar functions by using a cross species approach. Both are intrinsically disordered proteins, which rapidly changed their sequence during evolution. Moreover, both proteins still interact with conserved components of the germ cell specification pathway. These data might provide a first example of two proteins with the same biological role, but distinct sequence.

Immortalization of common marmoset monkey fibroblasts by piggyBac transposition of hTERT

Following a certain type-specific number of mitotic divisions, terminally differentiated cells undergo proliferative senescence, thwarting efforts to expand different cell populations in vitro for the needs of scientific research or medical therapies. The primary cause of this phenomenon is the progressive shortening of the telomeres and the subsequent activation of cell cycle control pathways leading to a block of cell proliferation. Restoration of telomere length by transgenic expression of telomerase reverse transcriptase (TERT) usually results in bypassing of the replicative senescence and ultimately in cell immortalization. To date, there have not been any reports regarding immortalization of cells from common marmoset (Callithrix jacchus), an important non-human primate model for various human diseases, with the use of exogenous human TERT (hTERT). In this study, marmoset fibroblasts were successfully immortalized with transposon-integrated transgenic hTERT and expanded in vitro for over 500 population doublings. Calculation of population doubling levels (PDL) showed that the derived hTERT-transgenic lines had significantly higher proliferation potential than the wild-type fibroblasts, which reached only a maximum of 46 doublings. However, the immortalized cells exhibited differences in the morphology compared with the control fibroblasts and transcriptome analysis also revealed changes in the gene expression patterns. Finally, the karyotypes of all hTERT-transgenic cell lines showed various aberrations such as presence of extra Chromosome 17, isochromosome 21q, or tetraploidy. By single-cell expansion of the least affected monoclonal immortalized line, one sub-clonal line with normal karyotype was established, suggesting the possibility to derive immortal marmoset cells with normal karyotypes. The results of this study are an important step towards the development and optimization of methods for the production of immortalized cells from common marmoset monkeys.

Neurons under T Cell Attack Coordinate Phagocyte-Mediated Synaptic Stripping

Inflammatory disorders of the CNS are frequently accompanied by synaptic loss, which is thought to involve phagocytic microglia and complement components. However, the mechanisms accounting for aberrant synaptic connectivity in the context of CD8⁺ T cell-driven neuronal damage are poorly understood. Here, we profiled the neuronal translatome in a murine model of encephalitis caused by CD8⁺ T cells targeting antigenic neurons. Neuronal STAT1 signaling and downstream CCL2 expression were essential for apposition of phagocytes, ensuing synaptic loss and neurological disease. Analogous observations were made in the brains of Rasmussen's encephalitis patients. In this devastating CD8⁺ T cell-driven autoimmune disease, neuronal STAT1 phosphorylation and CCL2 expression co-clustered with infiltrating CD8⁺ T cells as well as phagocytes. Taken together, our findings uncover an active role of neurons in coordinating phagocyte-mediated synaptic loss and highlight neuronal STAT1 and CCL2 as critical steps in this process that are amenable to pharmacological interventions.

The DNA Methyltransferase 1 (DNMT1) Controls the Shape and Dynamics of Migrating POA-Derived Interneurons Fated for the Murine Cerebral Cortex

The proliferative niches in the subpallium generate a rich cellular variety fated for diverse telencephalic regions. The embryonic preoptic area (POA) represents one of these domains giving rise to the pool of cortical GABAergic interneurons and glial cells, in addition to striatal and residual POA cells. The migration from sites of origin within the subpallium to the distant targets like the cerebral cortex, accomplished by the adoption and maintenance of a particular migratory morphology, is a critical step during interneuron development. To identify factors orchestrating this process, we performed single-cell transcriptome analysis and detected Dnmt1 expression in murine migratory GABAergic POA-derived cells. Deletion of Dnmt1 in postmitotic immature cells of the POA caused defective migration and severely diminished adult cortical interneuron numbers. We found that DNA methyltransferase 1 (DNMT1) preserves the migratory shape in part through negative regulation of Pak6, which stimulates neuritogenesis at postmigratory stages. Our data underline the importance of DNMT1 for the migration of POA-derived cells including cortical interneurons.

Retinoic acid-induced expression of Hnf1b and Fzd4 is required for pancreas development in Xenopus laevis

Retinoic acid (RA) is required for pancreas specification in Xenopus and other vertebrates. However, the gene network that is directly induced by RA signalling in this context remains to be defined. By RNA sequencing of in vitro-generated pancreatic explants, we identified the genes encoding the transcription factor Hnf1β and the Wnt-receptor Fzd4/Fzd4s as direct RA target genes. Functional analyses of Hnf1b and Fzd4/Fzd4s in programmed pancreatic explants and whole embryos revealed their requirement for pancreatic progenitor formation and differentiation. Thus, Hnf1β and Fzd4/Fzd4s appear to be involved in pre-patterning events of the embryonic endoderm that allow pancreas formation in Xenopus.

The functional readthrough extension of malate dehydrogenase reveals a modification of the genetic code

Translational readthrough gives rise to C-terminally extended proteins, thereby providing the cell with new protein isoforms. These may have different properties from the parental proteins if the extensions contain functional domains. While for most genes amino acid incorporation at the stop codon is far lower than 0.1%, about 4% of malate dehydrogenase (MDH1) is physiologically extended by translational readthrough and the actual ratio of MDH1x (extended protein) to ‘normal' MDH1 is dependent on the cell type. In human cells, arginine and tryptophan are co-encoded by the MDH1x UGA stop codon. Readthrough is controlled by the 7-nucleotide high-readthrough stop codon context without contribution of the subsequent 50 nucleotides encoding the extension. All vertebrate MDH1x is directed to peroxisomes via a hidden peroxisomal targeting signal (PTS) in the readthrough extension, which is more highly conserved than the extension of lactate dehydrogenase B. The hidden PTS of non-mammalian MDH1x evolved to be more efficient than the PTS of mammalian MDH1x. These results provide insight into the genetic and functional co-evolution of these dually localized dehydrogenases.

Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

Hepatic gene therapy rescues high-fat diet responses in circadian Clock mutant mice

OBJECTIVE

Circadian Clock gene mutant mice show dampened 24-h feeding rhythms and an increased sensitivity to high-fat diet (HFD) feeding. Restricting HFD access to the dark phase counteracts its obesogenic effect in wild-type mice. The extent to which altered feeding rhythms are causative for the obesogenic phenotype of Clock mutant mice, however, remains unknown.

METHODS

Metabolic parameters of wild-type (WT) and ClockΔ19 mutant mice (MT) were investigated under ad libitum and nighttime restricted HFD feeding. Liver circadian clock function was partially rescued by hydrodynamic tail vein delivery of WT-Clock DNA vectors in mutant mice and transcriptional, metabolic, endocrine and behavioral rhythms studied.

RESULTS

Nighttime-restricted feeding restored food intake, but not body weight regulation in MT mice under HFD, suggesting Clock-dependent metabolic dysregulation downstream of circadian appetite control. Liver-directed Clock gene therapy partially restored liver circadian oscillator function and transcriptome regulation without affecting centrally controlled circadian behaviors. Under HFD, MT mice with partially restored liver clock function (MT-LR) showed normalized body weight gain, rescued 24-h food intake rhythms, and WT-like energy expenditure. This was associated with decreased nighttime leptin and daytime ghrelin levels, reduced hepatic lipid accumulation, and improved glucose tolerance. Transcriptome analysis revealed that hepatic Clock rescue in MT mice affected a range of metabolic pathways.

CONCLUSION

Liver Clock gene therapy improves resistance against HFD-induced metabolic impairments in mice with circadian clock disruption. Restoring or stabilizing liver clock function might be a promising target for therapeutic interventions in obesity and metabolic disorders.

mRNA quality control is bypassed for immediate export of stress-responsive transcripts

Cells grow well only in a narrow range of physiological conditions. Surviving extreme conditions requires the instantaneous expression of chaperones that help to overcome stressful situations. To ensure the preferential synthesis of these heat-shock proteins, cells inhibit transcription, pre-mRNA processing and nuclear export of non-heat-shock transcripts, while stress-specific mRNAs are exclusively exported and translated. How cells manage the selective retention of regular transcripts and the simultaneous rapid export of heat-shock mRNAs is largely unknown. In Saccharomyces cerevisiae, the shuttling RNA adaptor proteins Npl3, Gbp2, Hrb1 and Nab2 are loaded co-transcriptionally onto growing pre-mRNAs. For nuclear export, they recruit the export-receptor heterodimer Mex67-Mtr2 (TAP-p15 in humans). Here we show that cellular stress induces the dissociation of Mex67 and its adaptor proteins from regular mRNAs to prevent general mRNA export. At the same time, heat-shock mRNAs are rapidly exported in association with Mex67, without the need for adapters. The immediate co-transcriptional loading of Mex67 onto heat-shock mRNAs involves Hsf1, a heat-shock transcription factor that binds to heat-shock-promoter elements in stress-responsive genes. An important difference between the export modes is that adaptor-protein-bound mRNAs undergo quality control, whereas stress-specific transcripts do not. In fact, regular mRNAs are converted into uncontrolled stress-responsive transcripts if expressed under the control of a heat-shock promoter, suggesting that whether an mRNA undergoes quality control is encrypted therein. Under normal conditions, Mex67 adaptor proteins are recruited for RNA surveillance, with only quality-controlled mRNAs allowed to associate with Mex67 and leave the nucleus. Thus, at the cost of error-free mRNA formation, heat-shock mRNAs are exported and translated without delay, allowing cells to survive extreme situations.

The SCN Clock Governs Circadian Transcription Rhythms in Murine Epididymal White Adipose Tissue

The circadian master pacemaker in the suprachiasmatic nucleus (SCN) orchestrates peripheral clocks in various organs and synchronizes them with external time, including those in adipose tissue, which displays circadian oscillations in various metabolic and endocrine outputs. Because our knowledge about the instructive role of the SCN clock on peripheral tissue function is based mainly on SCN lesion studies, we here used an alternative strategy employing the Cre/ loxP system to functionally delete the SCN clock in mice. We performed whole-genome microarray hybridizations of murine epididymal white adipose tissue (eWAT) RNA preparations to characterize the role of the SCN clock in eWAT circadian transcriptome regulation. Most of the rhythmic transcripts in control animals were not rhythmic in SCN mutants, but a significant number of transcripts were rhythmic only in mutant eWAT. Core clock genes were rhythmic in both groups, but as was reported before for other tissues, rhythms were dampened and phase advanced in mutant animals. In SCN-mutant mice, eWAT lost the rhythm of metabolic pathway-related transcripts, while transcripts gaining rhythms in SCN-mutant mice were associated with various immune functions. These data reveal a complex interaction of SCN-derived and local circadian signals in the regulation of adipose transcriptome programs.

Identification of New Fungal Peroxisomal Matrix Proteins and Revision of the PTS1 Consensus

The peroxisomal targeting signal type 1 (PTS1) is a seemingly simple peptide sequence at the C-terminal end of most peroxisomal matrix proteins. PTS1 can be described as a tripeptide with the consensus motif [S/A/C] [K/R/H] L. However, this description is neither necessary nor sufficient. It does not cover all cases of PTS1 proteins, and some proteins in accordance with this consensus do not target to the peroxisome. In order to find new PTS proteins in yeast and to arrive at a more complete description of the PTS1 consensus motif, we developed a machine learning approach that involves orthologue expansion of the set of known peroxisomal proteins. We performed a genome-wide in silico screen, characterised several PTS1-containing peptides and identified two new peroxisomal matrix proteins, which we named Pxp1 (Yel020c) and Pxp2 (Yjr111c). Based on these in silico and in vivo analyses, we revised the yeast PTS1 consensus which now includes all known PTS1 proteins.

The transcriptomes of novel marmoset monkey embryonic stem cell lines reflect distinct genomic features

Embryonic stem cells (ESCs) are useful for the study of embryonic development. However, since research on naturally conceived human embryos is limited, non-human primate (NHP) embryos and NHP ESCs represent an excellent alternative to the corresponding human entities. Though, ESC lines derived from naturally conceived NHP embryos are still very rare. Here, we report the generation and characterization of four novel ESC lines derived from natural preimplantation embryos of the common marmoset monkey (Callithrix jacchus). For the first time we document derivation of NHP ESCs derived from morula stages. We show that quantitative chromosome-wise transcriptome analyses precisely reflect trisomies present in both morula-derived ESC lines. We also demonstrate that the female ESC lines exhibit different states of X-inactivation which is impressively reflected by the abundance of the lncRNA X inactive-specific transcript (XIST). The novel marmoset ESC lines will promote basic primate embryo and ESC studies as well as preclinical testing of ESC-based regenerative approaches in NHP.

Characterization, prediction and evolution of plant peroxisomal targeting signals type 1 (PTS1s)

Our knowledge of the proteome of plant peroxisomes and their functional plasticity is far from being complete, primarily due to major technical challenges in experimental proteome research of the fragile cell organelle. Several unexpected novel plant peroxisome functions, for instance in biotin and phylloquinone biosynthesis, have been uncovered recently. Nevertheless, very few regulatory and membrane proteins of plant peroxisomes have been identified and functionally described up to now. To define the matrix proteome of plant peroxisomes, computational methods have emerged as important powerful tools. Novel prediction approaches of high sensitivity and specificity have been developed for peroxisome targeting signals type 1 (PTS1) and have been validated by in vivo subcellular targeting analyses and thermodynamic binding studies with the cytosolic receptor, PEX5. Accordingly, the algorithms allow the correct prediction of many novel peroxisome-targeted proteins from plant genome sequences and the discovery of additional organelle functions. In this review, we provide an overview of methodologies, capabilities and accuracies of available prediction algorithms for PTS1 carrying proteins. We also summarize and discuss recent quantitative, structural and mechanistic information of the interaction of PEX5 with PTS1 carrying proteins in relation to in vivo import efficiency. With this knowledge, we develop a model of how proteins likely evolved peroxisomal targeting signals in the past and still nowadays, in which order the two import pathways might have evolved in the ancient eukaryotic cell, and how the secondary loss of the PTS2 pathway probably happened in specific organismal groups.

MiR144/451 Expression Is Repressed by RUNX1 During Megakaryopoiesis and Disturbed by RUNX1/ETO

A network of lineage-specific transcription factors and microRNAs tightly regulates differentiation of hematopoietic stem cells along the distinct lineages. Deregulation of this regulatory network contributes to impaired lineage fidelity and leukemogenesis. We found that the hematopoietic master regulator RUNX1 controls the expression of certain microRNAs, of importance during erythroid/megakaryocytic differentiation. In particular, we show that the erythorid miR144/451 cluster is epigenetically repressed by RUNX1 during megakaryopoiesis. Furthermore, the leukemogenic RUNX1/ETO fusion protein transcriptionally represses the miR144/451 pre-microRNA. Thus RUNX1/ETO contributes to increased expression of miR451 target genes and interferes with normal gene expression during differentiation. Furthermore, we observed that inhibition of RUNX1/ETO in Kasumi1 cells and in RUNX1/ETO positive primary acute myeloid leukemia patient samples leads to up-regulation of miR144/451. RUNX1 thus emerges as a key regulator of a microRNA network, driving differentiation at the megakaryocytic/erythroid branching point. The network is disturbed by the leukemogenic RUNX1/ETO fusion product.

SMRT sequencing of the Campylobacter coli BfR-CA-9557 genome sequence reveals unique methylation motifs

BACKGROUND

Campylobacter species are the most prevalent bacterial pathogen causing acute enteritis worldwide. In contrast to Campylobacter jejuni, about 5 % of Campylobacter coli strains exhibit susceptibility to restriction endonuclease digestion by DpnI cutting specifically 5'-G(m)ATC-3' motifs. This indicates significant differences in DNA methylation between both microbial species. The goal of the study was to analyze the methylome of a C. coli strain susceptible to DpnI digestion, to identify its methylation motifs and restriction modification systems (RM-systems), and compare them to related organisms like C. jejuni and Helicobacter pylori.

RESULTS

Using one SMRT cell and the PacBio RS sequencing technology followed by PacBio Modification and Motif Analysis the complete genome of the DpnI susceptible strain C. coli BfR-CA-9557 was sequenced to 500-fold coverage and assembled into a single contig of 1.7 Mbp. The genome contains a CJIE1-like element prophage and is phylogenetically closer to C. coli clade 1 isolates than clade 3. 45,881 6-methylated adenines (ca. 2.7 % of genome positions) that are predominantly arranged in eight different methylation motifs and 1,788 4-methylated cytosines (ca. 0.1 %) have been detected. Only two of these motifs correspond to known restriction modification motifs. Characteristic for this methylome was the very high fraction of methylation of motifs with mostly above 99 %.

CONCLUSIONS

Only five dominant methylation motifs have been identified in C. jejuni, which have been associated with known RM-systems. C. coli BFR-CA-9557 shares one (RAATTY) of these, but four ORFs could be assigned to putative Type I RM-systems, seven ORFs to Type II RM-systems and three ORFs to Type IV RM-systems. In accordance with DpnI prescreening RM-system IIP, methylation of GATC motifs was detected in C. coli BfR-CA-9557. A homologous IIP RM-system has been described for H. pylori. The remaining methylation motifs are specific for C. coli BfR-CA-9557 and have been neither detected in C. jejuni nor in H. pylori. The results of this study give us new insights into epigenetics of Campylobacteraceae and provide the groundwork to resolve the function of RM-systems in C. coli.

Global analysis of asymmetric RNA enrichment in oocytes reveals low conservation between closely related Xenopus species

Subcellular localization of mRNAs contributes to the generation of cellular asymmetries and cell fate determination. A comparative global analysis is given of animally and vegetally enriched RNAs in oocytes from two closely related Xenopus species.

RNAs that localize to the vegetal cortex during Xenopus laevis oogenesis have been reported to function in germ layer patterning, axis determination, and development of the primordial germ cells. Here we report on the genome-wide, comparative analysis of differentially localizing RNAs in Xenopus laevis and Xenopus tropicalis oocytes, revealing a surprisingly weak degree of conservation in respect to the identity of animally as well as vegetally enriched transcripts in these closely related species. Heterologous RNA injections and protein binding studies indicate that the different RNA localization patterns in these two species are due to gain/loss of cis-acting localization signals rather than to differences in the RNA-localizing machinery.

Thymocyte-derived BDNF influences T-cell maturation at the DN3/DN4 transition stage

Brain-derived neurotrophic factor (BDNF) promotes neuronal survival, regeneration, and plasticity. Emerging evidence also indicates an essential role for BDNF outside the nervous system, for instance in immune cells. We therefore investigated the impact of BDNF on T cells using BDNF knockout (KO) mice and conditional KO mice lacking BDNF specifically in this lymphoid subset. In both settings, we observed diminished T-cell cellularity in peripheral lymphoid organs and an increase in CD4(+) CD44(+) memory T cells. Analysis of thymocyte development revealed diminished total thymocyte numbers, accompanied by a significant increase in CD4/CD8 double-negative (DN) thymocytes due to a partial block in the transition from the DN3 to the DN4 stage. This was neither due to increased thymocyte apoptosis nor defects in the expression of the TCR-β chain or the pre-TCR. In contrast, pERK but not pAKT levels were diminished in DN3 BDNF-deficient thymocytes. BDNF deficiency in T cells did not result in gross deficits in peripheral acute immune responses nor in changes of the homeostatic proliferation of peripheral T cells. Taken together, our data reveal a critical autocrine and/or paracrine role of T-cell-derived BDNF in thymocyte maturation involving ERK-mediated TCR signaling pathways.

Peroxisomal lactate dehydrogenase is generated by translational readthrough in mammals

Translational readthrough gives rise to low abundance proteins with C-terminal extensions beyond the stop codon. To identify functional translational readthrough, we estimated the readthrough propensity (RTP) of all stop codon contexts of the human genome by a new regression model in silico, identified a nucleotide consensus motif for high RTP by using this model, and analyzed all readthrough extensions in silico with a new predictor for peroxisomal targeting signal type 1 (PTS1). Lactate dehydrogenase B (LDHB) showed the highest combined RTP and PTS1 probability. Experimentally we show that at least 1.6% of the total cellular LDHB is targeted to the peroxisome by a conserved hidden PTS1. The readthrough-extended lactate dehydrogenase subunit LDHBx can also co-import LDHA, the other LDH subunit, into peroxisomes. Peroxisomal LDH is conserved in mammals and likely contributes to redox equivalent regeneration in peroxisomes.

DOI:http://dx.doi.org/10.7554/eLife.03640.001

Amino acids are the building blocks of proteins, and the order of the amino acids in a protein is determined by the order in which ‘codons’ appear in a messenger RNA molecule. Most codons represent a specific amino acid, but there are also three stop codons that are used to mark the end of a protein.

When the cellular machinery that ‘translates’ the messenger RNA molecule into a protein encounters a stop codon, it stops and releases the completed protein. Sometimes, however, the stop codon is not interpreted as a stop signal, and the translation of the messenger RNA molecule continues until another stop codon is encountered. This process is known as readthrough.

Some organisms, in particular viruses and fungi, use readthrough to produce a wider range of proteins than their genomes would otherwise allow. While readthrough also occurs in higher organisms such as mammals, it is not known if the resulting proteins perform extra functions that the original protein does not perform.

A number of factors affect whether readthrough occurs when an mRNA template is being translated. For example, each of the three stop codons has a different likelihood of having its stop signal misinterpreted, and the mRNA sequence that surrounds the stop codon can also affect the likelihood of readthrough.

Schueren et al. have developed a computational model that estimates how common this form of translational readthrough is in the human genome. The model was based on the identity of the stop codons themselves and the surrounding mRNA sequence. This model was then combined with another model that identifies proteins that are targeted to a structure inside a cell called the peroxisome, which is where a number of essential energy-releasing reactions take place. The combined model enabled Schueren et al. to identify proteins that both perform functions in the peroxisome and are likely to be formed by readthrough.

The combined model suggested a protein that is a part of lactate dehydrogenase: an enzyme that speeds up chemical reactions that are important for the cell to produce energy. Low levels of lactate dehydrogenase had previously been found in the peroxisome, despite it apparently lacking a specific sequence of amino acids that proteins need to have to enter the peroxisome. However, Schueren et al. confirmed experimentally that readthrough does occur for the lactate dehydrogenase component identified by the model, revealing that it contains a ‘hidden’ peroxisome-targeting region. Furthermore, when more translational readthrough occurred, more lactate dehydrogenase was found in the peroxisomes.

This unusual way that lactate dehydrogenase enters the peroxisome is an example of how the cell optimizes the used of the genetic information encoded in the genome and in messenger RNA. Translational readthrough always ensures that a certain proportion of lactate dehydrogenase will be brought to the peroxisome. The computational model developed here will be a valuable tool to identify other such proteins produced from genomes, including the human genome and those of other species.

DOI:http://dx.doi.org/10.7554/eLife.03640.002

Protein signature-based estimation of metagenomic abundances including all domains of life and viruses

Motivation: Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included in taxonomic profiling. Such a full-range approach, however, is difficult to realize owing to the limited coverage of available reference data. In particular, archaea and viruses are generally not well represented by current genome databases.

Results: We introduce a novel approach to taxonomic profiling of metagenomes that is based on mixture model analysis of protein signatures. Our results on simulated and real data reveal the difficulties of the existing methods when measuring achaeal or viral abundances and show the overall good profiling performance of the protein-based mixture model. As an application example, we provide a large-scale analysis of data from the Human Microbiome Project. This demonstrates the utility of our method as a first instance profiling tool for a fast estimate of the community structure.

Availability:http://gobics.de/TaxyPro.

Contact:pmeinic@gwdg.de

Supplementary information:Supplementary Material is available at Bioinformatics online.

PredPlantPTS1: A Web Server for the Prediction of Plant Peroxisomal Proteins

Prediction of subcellular protein localization is essential to correctly assign unknown proteins to cell organelle-specific protein networks and to ultimately determine protein function. For metazoa, several computational approaches have been developed in the past decade to predict peroxisomal proteins carrying the peroxisome targeting signal type 1 (PTS1). However, plant-specific PTS1 protein prediction methods have been lacking up to now, and pre-existing methods generally were incapable of correctly predicting low-abundance plant proteins possessing non-canonical PTS1 patterns. Recently, we presented a machine learning approach that is able to predict PTS1 proteins for higher plants (spermatophytes) with high accuracy and which can correctly identify unknown targeting patterns, i.e., novel PTS1 tripeptides and tripeptide residues. Here we describe the first plant-specific web server PredPlantPTS1 for the prediction of plant PTS1 proteins using the above-mentioned underlying models. The server allows the submission of protein sequences from diverse spermatophytes and also performs well for mosses and algae. The easy-to-use web interface provides detailed output in terms of (i) the peroxisomal targeting probability of the given sequence, (ii) information whether a particular non-canonical PTS1 tripeptide has already been experimentally verified, and (iii) the prediction scores for the single C-terminal 14 amino acid residues. The latter allows identification of predicted residues that inhibit peroxisome targeting and which can be optimized using site-directed mutagenesis to raise the peroxisome targeting efficiency. The prediction server will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants. PredPlantPTS1 is freely accessible at ppp.gobics.de.

Non-canonical peroxisome targeting signals: identification of novel PTS1 tripeptides and characterization of enhancer elements by computational permutation analysis

BACKGROUND

High-accuracy prediction tools are essential in the post-genomic era to define organellar proteomes in their full complexity. We recently applied a discriminative machine learning approach to predict plant proteins carrying peroxisome targeting signals (PTS) type 1 from genome sequences. For Arabidopsis thaliana 392 gene models were predicted to be peroxisome-targeted. The predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal.

RESULTS

In this study, we experimentally validated the predictions in greater depth by focusing on the most challenging Arabidopsis proteins with unknown non-canonical PTS1 tripeptides and prediction scores close to the threshold. By in vivo subcellular targeting analysis, three novel PTS1 tripeptides (QRL>, SQM>, and SDL>) and two novel tripeptide residues (Q at position -3 and D at pos. -2) were identified. To understand why, among many Arabidopsis proteins carrying the same C-terminal tripeptides, these proteins were specifically predicted as peroxisomal, the residues upstream of the PTS1 tripeptide were computationally permuted and the changes in prediction scores were analyzed. The newly identified Arabidopsis proteins were found to contain four to five amino acid residues of high predicted targeting enhancing properties at position -4 to -12 in front of the non-canonical PTS1 tripeptide. The identity of the predicted targeting enhancing residues was unexpectedly diverse, comprising besides basic residues also proline, hydroxylated (Ser, Thr), hydrophobic (Ala, Val), and even acidic residues.

CONCLUSIONS

Our computational and experimental analyses demonstrate that the plant PTS1 tripeptide motif is more diverse than previously thought, including an increasing number of non-canonical sequences and allowed residues. Specific targeting enhancing elements can be predicted for particular sequences of interest and are far more diverse in amino acid composition and positioning than previously assumed. Machine learning methods become indispensable to predict which specific proteins, among numerous candidate proteins carrying the same non-canonical PTS1 tripeptide, contain sufficient enhancer elements in terms of number, positioning and total strength to cause peroxisome targeting.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

CoMet--a web server for comparative functional profiling of metagenomes

Analyzing the functional potential of newly sequenced genomes and metagenomes has become a common task in biomedical and biological research. With the advent of high-throughput sequencing technologies comparative metagenomics opens the way to elucidate the genetically determined similarities and differences of complex microbial communities. We developed the web server ‘CoMet’ (http://comet.gobics.de), which provides an easy-to-use comparative metagenomics platform that is well-suitable for the analysis of large collections of metagenomic short read data. CoMet combines the ORF finding and subsequent assignment of protein sequences to Pfam domain families with a comparative statistical analysis. Besides comprehensive tabular data files, the CoMet server also provides visually interpretable output in terms of hierarchical clustering and multi-dimensional scaling plots and thus allows a quick overview of a given set of metagenomic samples.

Mixture models for analysis of the taxonomic composition of metagenomes

Motivation: Inferring the taxonomic profile of a microbial community from a large collection of anonymous DNA sequencing reads is a challenging task in metagenomics. Because existing methods for taxonomic profiling of metagenomes are all based on the assignment of fragmentary sequences to phylogenetic categories, the accuracy of results largely depends on fragment length. This dependence complicates comparative analysis of data originating from different sequencing platforms or resulting from different preprocessing pipelines.

Results: We here introduce a new method for taxonomic profiling based on mixture modeling of the overall oligonucleotide distribution of a sample. Our results indicate that the mixture-based profiles compare well with taxonomic profiles obtained with other methods. However, in contrast to the existing methods, our approach shows a nearly constant profiling accuracy across all kinds of read lengths and it operates at an unrivaled speed.

Availability: A platform-independent implementation of the mixture modeling approach is available in terms of a MATLAB/Octave toolbox at http://gobics.de/peter/taxy. In addition, a prototypical implementation within an easy-to-use interactive tool for Windows can be downloaded.

Contact:pmeinic@gwdg.de; thomas@gobics.de

Supplementary Information:Supplementary data are available at Bioinformatics online.

Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses

In the postgenomic era, accurate prediction tools are essential for identification of the proteomes of cell organelles. Prediction methods have been developed for peroxisome-targeted proteins in animals and fungi but are missing specifically for plants. For development of a predictor for plant proteins carrying peroxisome targeting signals type 1 (PTS1), we assembled more than 2500 homologous plant sequences, mainly from EST databases. We applied a discriminative machine learning approach to derive two different prediction methods, both of which showed high prediction accuracy and recognized specific targeting-enhancing patterns in the regions upstream of the PTS1 tripeptides. Upon application of these methods to the Arabidopsis thaliana genome, 392 gene models were predicted to be peroxisome targeted. These predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. The prediction methods were able to correctly infer novel PTS1 tripeptides, which even included novel residues. Twenty-three newly predicted PTS1 tripeptides were experimentally confirmed, and a high variability of the plant PTS1 motif was discovered. These prediction methods will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants.

Predicting phenotypic traits of prokaryotes from protein domain frequencies

Background

Establishing the relationship between an organism's genome sequence and its phenotype is a fundamental challenge that remains largely unsolved. Accurately predicting microbial phenotypes solely based on genomic features will allow us to infer relevant phenotypic characteristics when the availability of a genome sequence precedes experimental characterization, a scenario that is favored by the advent of novel high-throughput and single cell sequencing techniques.

Results

We present a novel approach to predict the phenotype of prokaryotes directly from their protein domain frequencies. Our discriminative machine learning approach provides high prediction accuracy of relevant phenotypes such as motility, oxygen requirement or spore formation. Moreover, the set of discriminative domains provides biological insight into the underlying phenotype-genotype relationship and enables deriving hypotheses on the possible functions of uncharacterized domains.

Conclusions

Fast and accurate prediction of microbial phenotypes based on genomic protein domain content is feasible and has the potential to provide novel biological insights. First results of a systematic check for annotation errors indicate that our approach may also be applied to semi-automatic correction and completion of the existing phenotype annotation.

Orphelia: predicting genes in metagenomic sequencing reads

Metagenomic sequencing projects yield numerous sequencing reads of a diverse range of uncultivated and mostly yet unknown microorganisms. In many cases, these sequencing reads cannot be assembled into longer contigs. Thus, gene prediction tools that were originally developed for whole-genome analysis are not suitable for processing metagenomes. Orphelia is a program for predicting genes in short DNA sequences that is available through a web server application (http://orphelia.gobics.de). Orphelia utilizes prediction models that were created with machine learning techniques on the basis of a wide range of annotated genomes. In contrast to other methods for metagenomic gene prediction, Orphelia has fragment length-specific prediction models for the two most popular sequencing techniques in metagenomics, chain termination sequencing and pyrosequencing. These models ensure highly specific gene predictions.

MarVis: a tool for clustering and visualization of metabolic biomarkers

BACKGROUND

A central goal of experimental studies in systems biology is to identify meaningful markers that are hidden within a diffuse background of data originating from large-scale analytical intensity measurements as obtained from metabolomic experiments. Intensity-based clustering is an unsupervised approach to the identification of metabolic markers based on the grouping of similar intensity profiles. A major problem of this basic approach is that in general there is no prior information about an adequate number of biologically relevant clusters.

RESULTS

We present the tool MarVis (Marker Visualization) for data mining on intensity-based profiles using one-dimensional self-organizing maps (1D-SOMs). MarVis can import and export customizable CSV (Comma Separated Values) files and provides aggregation and normalization routines for preprocessing of intensity profiles that contain repeated measurements for a number of different experimental conditions. Robust clustering is then achieved by training of an 1D-SOM model, which introduces a similarity-based ordering of the intensity profiles. The ordering allows a convenient visualization of the intensity variations within the data and facilitates an interactive aggregation of clusters into larger blocks. The intensity-based visualization is combined with the presentation of additional data attributes, which can further support the analysis of experimental data.

CONCLUSION

MarVis is a user-friendly and interactive tool for exploration of complex pattern variation in a large set of experimental intensity profiles. The application of 1D-SOMs gives a convenient overview on relevant profiles and groups of profiles. The specialized visualization effectively supports researchers in analyzing a large number of putative clusters, even though the true number of biologically meaningful groups is unknown. Although MarVis has been developed for the analysis of metabolomic data, the tool may be applied to gene expression data as well.

Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps

Background

One of the goals of global metabolomic analysis is to identify metabolic markers that are hidden within a large background of data originating from high-throughput analytical measurements. Metabolite-based clustering is an unsupervised approach for marker identification based on grouping similar concentration profiles of putative metabolites. A major problem of this approach is that in general there is no prior information about an adequate number of clusters.

Results

We present an approach for data mining on metabolite intensity profiles as obtained from mass spectrometry measurements. We propose one-dimensional self-organizing maps for metabolite-based clustering and visualization of marker candidates. In a case study on the wound response of Arabidopsis thaliana, based on metabolite profile intensities from eight different experimental conditions, we show how the clustering and visualization capabilities can be used to identify relevant groups of markers.

Conclusion

Our specialized realization of self-organizing maps is well-suitable to gain insight into complex pattern variation in a large set of metabolite profiles. In comparison to other methods our visualization approach facilitates the identification of interesting groups of metabolites by means of a convenient overview on relevant intensity patterns. In particular, the visualization effectively supports researchers in analyzing many putative clusters when the true number of biologically meaningful groups is unknown.

Word correlation matrices for protein sequence analysis and remote homology detection

Background

Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provide the most accurate results. However, kernel-based methods often lack an interpretable model for analysis of discriminative sequence features, and predictions on new sequences usually are computationally expensive.

Results

In this work we present a novel kernel for protein sequences based on average word similarity between two sequences. We show that this kernel gives rise to a feature space that allows analysis of discriminative features and fast classification of new sequences. We demonstrate the performance of our approach on a widely-used benchmark setup for protein remote homology detection.

Conclusion

Our word correlation approach provides highly competitive performance as compared with state-of-the-art methods for protein remote homology detection. The learned model is interpretable in terms of biologically meaningful features. In particular, analysis of discriminative words allows the identification of characteristic regions in biological sequences. Because of its high computational efficiency, our method can be applied to ranking of potential homologs in large databases.

Remote homology detection based on oligomer distances

MOTIVATION

Remote homology detection is among the most intensively researched problems in bioinformatics. Currently discriminative approaches, especially kernel-based methods, provide the most accurate results. However, kernel methods also show several drawbacks: in many cases prediction of new sequences is computationally expensive, often kernels lack an interpretable model for analysis of characteristic sequence features, and finally most approaches make use of so-called hyperparameters which complicate the application of methods across different datasets.

RESULTS

We introduce a feature vector representation for protein sequences based on distances between short oligomers. The corresponding feature space arises from distance histograms for any possible pair of K-mers. Our distance-based approach shows important advantages in terms of computational speed while on common test data the prediction performance is highly competitive with state-of-the-art methods for protein remote homology detection. Furthermore the learnt model can easily be analyzed in terms of discriminative features and in contrast to other methods our representation does not require any tuning of kernel hyperparameters.

AVAILABILITY

Normalized kernel matrices for the experimental setup can be downloaded at www.gobics.de/thomas. Matlab code for computing the kernel matrices is available upon request.

CONTACT

thomas@gobics.de, peter@gobics.de.

BCI Competition 2003—Data Set IIb: Support Vector Machines for the P300 Speller Paradigm

We propose an approach to analyze data from the P300 speller paradigm using the machine-learning technique support vector machines. In a conservative classification scheme, we found the correct solution after five repetitions. While the classification within the competition is designed for offline analysis, our approach is also well-suited for a real-world online solution: It is fast, requires only 10 electrode positions and demands only a small amount of preprocessing.