BACKGROUND: Diastolic dysfunction is a poorly understood but clinically pervasive syndrome that is characterized by increased diastolic stiffness. Titin is the main determinant of cellular passive stiffness. However, the physiological role that the tandem immunoglobulin (Ig) segment of titin plays in stiffness generation and whether shortening this segment is sufficient to cause diastolic dysfunction need to be established. METHODS AND RESULTS: We generated a mouse model in which 9 Ig-like domains (Ig3-Ig11) were deleted from the proximal tandem Ig segment of the spring region of titin (IG KO). Exon microarray analysis revealed no adaptations in titin splicing, whereas novel phospho-specific antibodies did not detect changes in titin phosphorylation. Passive myocyte stiffness was increased in the IG KO, and immunoelectron microscopy revealed increased extension of the remaining titin spring segments as the sole likely underlying mechanism. Diastolic stiffness was increased at the tissue and organ levels, with no consistent changes in extracellular matrix composition or extracellular matrix-based passive stiffness, supporting a titin-based mechanism for in vivo diastolic dysfunction. Additionally, IG KO mice have a reduced exercise tolerance, a phenotype often associated with diastolic dysfunction. CONCLUSIONS: Increased titin-based passive stiffness is sufficient to cause diastolic dysfunction with exercise intolerance.

Detection of protein homology via sequence similarity has important applications in biology, from protein structure and function prediction to reconstruction of phylogenies. Although current methods for aligning protein sequences are powerful, challenges remain, including problems with homologous overextension of alignments and with regions under convergent evolution. Here, we test the ability of the profile hidden Markov model method HMMER3 to correctly assign homologous sequences to >13,000 manually curated families from the Pfam database. We identify problem families using protein regions that match two or more Pfam families not currently annotated as related in Pfam. We find that HMMER3 E-value estimates seem to be less accurate for families that feature periodic patterns of compositional bias, such as the ones typically observed in coiled-coils. These results support the continued use of manually curated inclusion thresholds in the Pfam database, especially on the subset of families that have been identified as problematic in experiments such as these. They also highlight the need for developing new methods that can correct for this particular type of compositional bias.

A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements "covariance models" (CMs) for RNA homology search, which harness both sequence and structural conservation when searching for RNA homologs. Thanks to the added statistical signal inherent in the secondary structure conservation of many RNA families, Infernal is more powerful than sequence-only based methods such as BLAST and profile HMMs. Together with the Rfam database of CMs, Infernal is a useful tool for identifying RNAs in metagenomics data sets.

In vertebrates, primary sex determination refers to the decision within a bipotential organ precursor to differentiate as a testis or ovary. Bifurcation of organ fate begins between embryonic day (E) 11.0–E12.0 in mice and likely involves a dynamic transcription network that is poorly understood. To elucidate the first steps of sexual fate specification, we profiled the XX and XY gonad transcriptomes at fine granularity during this period and resolved cascades of gene activation and repression. C57BL/6J (B6) XY gonads showed a consistent  5-hour delay in the activation of most male pathway genes and repression of female pathway genes relative to 129S1/SvImJ, which likely explains the sensitivity of the B6 strain to male-to-female sex reversal. Using this fine time course data, we predicted novel regulatory genes underlying expression QTLs (eQTLs) mapped in a previous study. To test predictions, we developed an in vitro gonad primary cell assay and optimized a lentivirus-based shRNA delivery method to silence candidate genes and quantify effects on putative targets. We provide strong evidence that Lmo4 (Lim-domain only 4) is a novel regulator of sex determination upstream of SF1 (Nr5a1), Sox9, Fgf9, and Col9a3. This approach can be readily applied to identify regulatory interactions in other systems.

Any method for RNA secondary structure prediction is determined by four ingredients. The architecture is the choice of features implemented by the model (such as stacked basepairs, loop length distributions, etc.). The architecture determines the number of parameters in the model. The scoring scheme is the nature of those parameters (whether thermodynamic, probabilistic, or weights). The parameterization stands for the specific values assigned to the parameters. These three ingredients are referred to as "the model." The fourth ingredient is the folding algorithms used to predict plausible secondary structures given the model and the sequence of a structural RNA. Here, I make several unifying observations drawn from looking at more than 40 years of methods for RNA secondary structure prediction in the light of this classification. As a final observation, there seems to be a performance ceiling that affects all methods with complex architectures, a ceiling that impacts all scoring schemes with remarkable similarity. This suggests that modeling RNA secondary structure by using intrinsic sequence-based plausible "foldability" will require the incorporation of other forms of information in order to constrain the folding space and to improve prediction accuracy. This could give an advantage to probabilistic scoring systems since a probabilistic framework is a natural platform to incorporate different sources of information into one single inference problem.

We tested whether transcription activator-like effectors (TALEs) could mediate repression and activation of endogenous enhancers in the Drosophila genome. TALE repressors (TALERs) targeting each of the five even-skipped (eve) stripe enhancers generated repression specifically of the focal stripes. TALE activators (TALEAs) targeting the eve promoter or enhancers caused increased expression primarily in cells normally activated by the promoter or targeted enhancer, respectively. This effect supports the view that repression acts in a dominant fashion on transcriptional activators and that the activity state of an enhancer influences TALE binding or the ability of the VP16 domain to enhance transcription. In these assays, the Hairy repression domain did not exhibit previously described long-range transcriptional repression activity. The phenotypic effects of TALER and TALEA expression in larvae and adults are consistent with the observed modulations of eve expression. TALEs thus provide a novel tool for detection and functional modulation of transcriptional enhancers in their native genomic context.

The brain represents sensory information in the coordinated activity of neuronal ensembles. Although the microcircuits underlying olfactory processing are well characterized in Drosophila, no studies to date have examined the encoding of odor identity by populations of neurons and related it to the odor specificity of olfactory behavior. Here we used two-photon Ca(2+) imaging to record odor-evoked responses from >100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity. Using a series of increasingly similar odor blends, we identified conditions in which odor discrimination is difficult behaviorally. We found that MB ensemble responses accounted well for olfactory acuity in this task. Kenyon cell ensembles with as few as 25 cells were sufficient to match behavioral discrimination accuracy. Using a generalization task, we demonstrated that the MB population code could predict the flies' responses to novel odors. The degree to which flies generalized a learned aversive association to unfamiliar test odors depended upon the relative similarity between the odors' evoked MB activity patterns. Discrimination and generalization place different demands on the animal, yet the flies' choices in these tasks were reliably predicted based on the amount of overlap between MB activity patterns. Therefore, these different behaviors can be understood in the context of a single physiological framework.

Serine hydrolases have diverse intracellular substrates, biological functions, and structural plasticity, and are thus important for biocatalyst design. Amongst serine hydrolases, the recently described ybfF enzyme family are promising novel biocatalysts with an unusual bifurcated substrate-binding cleft and the ability to recognize commercially relevant substrates. We characterized in detail the substrate selectivity of a novel ybfF enzyme from Vibrio cholerae (Vc-ybfF) by using a 21-member library of fluorogenic ester substrates. We assigned the roles of the two substrate-binding clefts in controlling the substrate selectivity and folded stability of Vc-ybfF by comprehensive substitution analysis. The overall substrate preference of Vc-ybfF was for short polar chains, but it retained significant activity with a range of cyclic and extended esters. This broad substrate specificity combined with the substitutional analysis demonstrates that the larger binding cleft controls the substrate specificity of Vc-ybfF. Key selectivity residues (Tyr116, Arg120, Tyr209) are also located at the larger binding pocket and control the substrate specificity profile. In the structure of ybfF the narrower binding cleft contains water molecules prepositioned for hydrolysis, but based on substitution this cleft showed only minimal contribution to catalysis. Instead, the residues surrounding the narrow binding cleft and at the entrance to the binding pocket contributed significantly to the folded stability of Vc-ybfF. The relative contributions of each cleft of the binding pocket to the catalytic activity and folded stability of Vc-ybfF provide a valuable map for designing future biocatalysts based on the ybfF scaffold.

Tsetse flies are viviparous insects that nurture a single intrauterine progeny per gonotrophic cycle. The developing larva is nourished by the lipid-rich, milk-like secretions from a modified female accessory gland (milk gland). An essential feature of the lactation process involves lipid mobilization for incorporation into the milk. In this study, we examined roles for juvenile hormone (JH) and insulin/IGF-like (IIS) signaling pathways during tsetse pregnancy. In particular, we examined the roles for these pathways in regulating lipid homeostasis during transitions between non-lactating (dry) and lactating periods. The dry period occurs over the course of oogenesis and embryogenesis, while the lactation period spans intrauterine larvigenesis. Genes involved in the JH and IIS pathways were upregulated during dry periods, correlating with lipid accumulation between bouts of lactation. RNAi suppression of Forkhead Box Sub Group O (FOXO) expression impaired lipolysis during tsetse lactation and reduced fecundity. Similar reduction of the JH receptor Methoprene tolerant (Met), but not its paralog germ cell expressed (gce), reduced lipid accumulation during dry periods, indicating functional divergence between Met and gce during tsetse reproduction. Reduced lipid levels following Met knockdown led to impaired fecundity due to inadequate fat reserves at the initiation of milk production. Both the application of the JH analog (JHA) methoprene and injection of insulin into lactating females increased stored lipids by suppressing lipolysis and reduced transcripts of lactation-specific genes, leading to elevated rates of larval abortion. To our knowledge, this study is the first to address the molecular physiology of JH and IIS in a viviparous insect, and specifically to provide a role for JH signaling through Met in the regulation of lipid metabolism during insect lactation.