A novel glycoside hydrolase 43-like enzyme from Clostridium boliviensis is an endo-xylanase and a candidate for xylooligosaccharide production from different xylan substrates

An uncharacterized gene encoding a glycoside hydrolase family 43-like enzyme from Clostridium boliviensis strain E-1 was identified from genomic sequence data, and the encoded enzyme, CbE1Xyn43-l, was produced in Escherichia coli. CbE1Xyn43-l (52.9 kDa) is a two-domain endo-β-xylanase consisting of a C-terminal CBM6 and a GH43-like catalytic domain. The positions of the catalytic dyad conserved in GH43, the catalytic base (Asp74), and proton donor (Glu240) were identified in alignments including GH43-enzymes of known 3D-structure from different subfamilies. CbE1Xyn43-l is active at pH 7.0-9.0, with optimum temperature at 65°C, and a more than 7 days' half-life in irreversible deactivation studies at this temperature. The enzyme hydrolyzed birchwood xylan, quinoa stalks glucuronoarabinoxylan, and wheat arabinoxylan with xylotriose and xylotetraose as major hydrolysis products. CbE1Xyn43-l also released xylobiose from pNPX2 with low turnover (kcat of 0.044 s-1) but was inactive on pNPX, showing that a degree of polymerization of three (DP3) was the smallest hydrolyzable substrate. Divalent ions affected the specific activity on xylan substrates, which dependent on the ion could be increased or decreased. In conclusion, CbE1Xyn43-l from C. boliviensis strain E-1 is the first characterized member of a large group of homologous hypothetical proteins annotated as GH43-like and is a thermostable endo-xylanase, producing xylooligosaccharides of high DP (xylotriose and xylotetraose) producer.

IMPORTANCE

The genome of Clostridium boliviensis strain E-1 encodes a number of hypothetical enzymes, annotated as glycoside hydrolase-like but not classified in the Carbohydrate Active Enzyme Database (CAZy). A novel thermostable GH43-like enzyme is here characterized as an endo-β-xylanase of interest in the production of prebiotic xylooligosaccharides (XOs) from different xylan sources. CbE1Xyn43-l is a two-domain enzyme composed of a catalytic GH43-l domain and a CBM6 domain, producing xylotriose as main XO product. The enzyme has homologs in many related Clostridium strains which may indicate a similar function and be a previously unknown type of endo-xylanase in this evolutionary lineage of microorganisms.

SPIRO - the automated Petri plate imaging platform designed by biologists, for biologists

Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.

Does a prior diagnosis of infectious disease confer an increased risk of latent autoimmune diabetes in adults?

AIMS

Infections are proposed risk factors for type 1 diabetes in children. We examined whether a diagnosis of infectious disease also confers an increased risk of latent autoimmune diabetes in adults (LADA).

MATERIALS AND METHODS

We used data from a population-based Swedish case-control study with incident cases of LADA (n = 597) and matched controls (n = 2386). The history of infectious disease was ascertained through national and regional patient registers. We estimated adjusted odds ratios (OR) with 95% confidence intervals for ≥1 respiratory (any/upper/lower), gastrointestinal, herpetic, other or any infectious disease episode, or separately, for 1 and ≥2 infectious disease episodes, within 0-1, 1-3, 3-5 and 5-10 years before LADA diagnosis/matching. Stratified analyses were performed on the basis of HLA risk genotypes and Glutamic acid decarboxylase antibodies (GADA) levels.

RESULTS

Individuals who developed LADA did not have a higher prevalence of infectious disease 1-10 years before diabetes diagnosis. For example, OR was estimated at 0.87 (0.66, 1.14) for any versus no respiratory infectious disease within 1-3 years. Similar results were seen for LADA with high-risk HLA genotypes (OR 0.95 [0.64, 1.42]) or high GADA levels (OR 1.10 [0.79, 1.55]), ≥2 episodes (OR 0.89 [0.56, 1.40]), and in infections treated using antibiotics (OR 1.03 [0.73, 1.45]). The only significant association was observed with lower respiratory disease the year preceding LADA diagnosis (OR 1.67 [1.06, 2.64]).

CONCLUSIONS

Our findings do not support the idea that exposure to infections increases the risk of LADA. A higher prevalence of respiratory infection in the year before LADA diagnosis could reflect increased susceptibility to infections due to hyperglycemia.

Intermolecular base-pairing interactions, a unique topology and exoribonuclease-resistant noncoding RNAs drive formation of viral chimeric RNAs in plants

In plants, exoribonuclease-resistant RNAs (xrRNAs) are produced by many viruses. Whereas xrRNAs contribute to the pathogenicity of these viruses, the role of xrRNAs in the virus infectious cycle remains elusive. Here, we show that xrRNAs produced by a benyvirus (a multipartite RNA virus with four genomic segments) in plants are involved in the formation of monocistronic coat protein (CP)-encoding chimeric RNAs. Naturally occurring chimeric RNAs, we discovered, are composed of 5'-end of RNA 2 and 3'-end of either RNA 3 or RNA 4 bearing conservative exoribonuclease-resistant 'coremin' region. Using computational tools and site-directed mutagenesis, we show that de novo formation of chimeric RNAs requires intermolecular base-pairing interaction between 'coremin' and 3'-proximal part of the CP gene of RNA 2 as well as a stem-loop structure immediately adjacent to the CP gene. Moreover, knockdown of the expression of the XRN4 gene, encoding 5'→3' exoribonuclease, inhibits biogenesis of both xrRNAs and chimeric RNAs. Our findings suggest a novel mechanism involving a unique tropology of the intermolecular base-pairing complex between xrRNAs and RNA2 to promote formation of chimeric RNAs in plants. XrRNAs, essential for chimeric RNA biogenesis, are generated through the action of cytoplasmic Xrn 4 5'→3' exoribonuclease conserved in all plant species.

Online tree expansion could help solve the problem of scalability in Bayesian phylogenetics

Bayesian phylogenetics is now facing a critical point. Over the last 20 years, Bayesian methods have reshaped phylogenetic inference and gained widespread popularity due to their high accuracy, the ability to quantify the uncertainty of inferences and the possibility of accommodating multiple aspects of evolutionary processes in the models that are used. Unfortunately, Bayesian methods are computationally expensive, and typical applications involve at most a few hundred sequences. This is problematic in the age of rapidly expanding genomic data and increasing scope of evolutionary analyses, forcing researchers to resort to less accurate but faster methods, such as maximum parsimony and maximum likelihood. Does this spell doom for Bayesian methods? Not necessarily. Here, we discuss some recently proposed approaches that could help scale up Bayesian analyses of evolutionary problems considerably. We focus on two particular aspects: online phylogenetics, where new data sequences are added to existing analyses, and alternatives to Markov chain Monte Carlo (MCMC) for scalable Bayesian inference. We identify 5 specific challenges and discuss how they might be overcome. We believe that online phylogenetic approaches and Sequential Monte Carlo hold great promise and could potentially speed up tree inference by orders of magnitude. We call for collaborative efforts to speed up the development of methods for real-time tree expansion through online phylogenetics.

Mechanism of TNFα-induced downregulation of salt-inducible kinase 2 in adipocytes

Salt-inducible kinase 2 (SIK2) is highly expressed in white adipocytes, but downregulated in individuals with obesity and insulin resistance. These conditions are often associated with a low-grade inflammation in adipose tissue. We and others have previously shown that SIK2 is downregulated by tumor necrosis factor α (TNFα), however, involvement of other pro-inflammatory cytokines, or the mechanisms underlying TNFα-induced SIK2 downregulation, remain to be elucidated. In this study we have shown that TNFα downregulates SIK2 protein expression not only in 3T3L1- but also in human in vitro differentiated adipocytes. Furthermore, monocyte chemoattractant protein-1 and interleukin (IL)-1β, but not IL-6, might also contribute to SIK2 downregulation during inflammation. We observed that TNFα-induced SIK2 downregulation occurred also in the presence of pharmacological inhibitors against several kinases involved in inflammation, namely c-Jun N-terminal kinase, mitogen activated protein kinase kinase 1, p38 mitogen activated protein kinase or inhibitor of nuclear factor kappa-B kinase (IKK). However, IKK may be involved in SIK2 regulation as we detected an increase of SIK2 when inhibiting IKK in the absence of TNFα. Increased knowledge about inflammation-induced downregulation of SIK2 could ultimately be used to develop strategies for the reinstalment of SIK2 expression in insulin resistance.

Proteome of airway surface liquid and mucus in newborn wildtype and cystic fibrosis piglets

BACKGROUND

The respiratory tract is protected from inhaled particles and microbes by mucociliary clearance, mediated by the mucus and the cilia creating a flow to move the mucus cephalad. Submucosal glands secrete linear MUC5B mucin polymers and because they pass through the gland duct before reaching the airway surface, bundled strands of 1000-5000 parallel molecules exit the glands. In contrast, the surface goblet cells secrete both MUC5AC and MUC5B.

METHODS

We used mass-spectrometry based proteomic analysis of unstimulated and carbachol stimulated newborn wild-type (WT) and cystic fibrosis transmembrane conductance regulator (CFTR) null (CF) piglet airways to study proteins in the airway surface liquid and mucus, to investigate if levels of MUC5AC and MUC5B were affected by carbachol stimulation and whether the proteins clustered according to function.

RESULTS

Proteins in the first four extracted fractions clustered together and the fifth fraction contained the mucus cluster, mucins and other proteins known to associate with mucins, whereas the traditional airway surface liquid proteins clustered to fraction 1-4 and were absent from the mucus fraction. Carbachol stimulation resulted in increased MUC5AC and MUC5B.

CONCLUSIONS

These results indicate a distinct separation between proteins in the washable surface liquid and the mucus fraction. In fractions 1-4 from newborn CF piglets an additional cluster containing acute phase proteins was observed, suggesting an early inflammatory response in CF piglets. Alternatively, increased levels of these proteins could indicate altered lung development in the CF piglets. This observation suggests that CF airway disease is present at birth and thus, treatment should commence directly after diagnosis.

Lessons from single-cell RNA sequencing of human islets

Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area.

Local temporal Rac1-GTP nadirs and peaks restrict cell protrusions and retractions

Cells probe their microenvironment using membrane protrusion-retraction cycles. Spatiotemporal coordination of Rac1 and RhoA GTP-binding activities initiates and reinforces protrusions and retractions, but the control of their finite lifetime remains unclear. We examined the relations of Rac1 and RhoA GTP-binding levels to key protrusion and retraction events, as well as to cell-ECM traction forces at physiologically relevant ECM stiffness. High RhoA-GTP preceded retractions and Rac1-GTP elevation before protrusions. Notable temporal Rac1-GTP nadirs and peaks occurred at the maximal edge velocity of local membrane protrusions and retractions, respectively, followed by declined edge velocity. Moreover, altered local Rac1-GTP consistently preceded similarly altered traction force. Local optogenetic Rac1-GTP perturbations defined a function of Rac1 in restricting protrusions and retractions and in promoting local traction force. Together, we show that Rac1 plays a fundamental role in restricting the size and durability of protrusions and retractions, plausibly in part through controlling traction forces.

Characterization of plasma lipidomics in adolescent subjects with increased risk for type 1 diabetes in the DiPiS cohort

INTRODUCTION

Type 1 diabetes (T1D) is caused by the destruction of pancreatic islet beta cells resulting in total loss of insulin production. Recent studies have suggested that the destruction may be interrelated to plasma lipids.

OBJECTIVES

Specific lipids have previously been shown to be decreased in children who develop T1D before four years of age. Disturbances of plasma lipids prior to clinical diagnosis of diabetes, if true, may provide a novel way to improve prediction, and monitor disease progression.

METHODS

A lipidomic approach was utilized to analyze plasma from 67 healthy adolescent subjects (10-15 years of age) with or without islet autoantibodies but all with increased genetic risk for T1D. The study subjects were enrolled at birth in the Diabetes Prediction in Skåne (DiPiS) study and after 10-15 years of follow-up we performed the present cross-sectional analysis. HLA-DRB345, -DRB1, -DQA1, -DQB1, -DPA1 and -DPB1 genotypes were determined using next generation sequencing. Lipidomic profiles were determined using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Lipidomics data were analyzed according to genotype.

RESULTS

Variation in levels of several specific phospholipid species were related to level of autoimmunity but not development of T1D. Five glycosylated ceramides were increased in insulin autoantibody (IAA) positive adolescent subjects compared to adolescent subjects without this autoantibody. Additionally, HLA genotypes seemed to influence levels of long chain triacylglycerol (TG).

CONCLUSION

Lipidomic profiling of adolescent subjects in high risk of T1D may improve sub-phenotyping in this high risk population.

A Shh/Gli-driven three-node timer motif controls temporal identity and fate of neural stem cells

How time is measured by neural stem cells during temporal neurogenesis has remained unresolved. By combining experiments and computational modeling, we define a Shh/Gli-driven three-node timer underlying the sequential generation of motor neurons (MNs) and serotonergic neurons in the brainstem. The timer is founded on temporal decline of Gli-activator and Gli-repressor activities established through down-regulation of Gli transcription. The circuitry conforms an incoherent feed-forward loop, whereby Gli proteins not only promote expression of Phox2b and thereby MN-fate but also account for a delayed activation of a self-promoting transforming growth factor-β (Tgfβ) node triggering a fate switch by repressing Phox2b. Hysteresis and spatial averaging by diffusion of Tgfβ counteract noise and increase temporal accuracy at the population level, providing a functional rationale for the intrinsically programmed activation of extrinsic switch signals in temporal patterning. Our study defines how time is reliably encoded during the sequential specification of neurons.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.

Irreversibility of T-Cell Specification: Insights from Computational Modelling of a Minimal Network Architecture

BACKGROUND/OBJECTIVES

A cascade of gene activations under the control of Notch signalling is required during T-cell specification, when T-cell precursors gradually lose the potential to undertake other fates and become fully committed to the T-cell lineage. We elucidate how the gene/protein dynamics for a core transcriptional module governs this important process by computational means.

METHODS

We first assembled existing knowledge about transcription factors known to be important for T-cell specification to form a minimal core module consisting of TCF-1, GATA-3, BCL11B, and PU.1 aiming at dynamical modeling. Model architecture was based on published experimental measurements of the effects on each factor when each of the others is perturbed. While several studies provided gene expression measurements at different stages of T-cell development, pure time series are not available, thus precluding a straightforward study of the dynamical interactions among these genes. We therefore translate stage dependent data into time series. A feed-forward motif with multiple positive feed-backs can account for the observed delay between BCL11B versus TCF-1 and GATA-3 activation by Notch signalling. With a novel computational approach, all 32 possible interactions among Notch signalling, TCF-1, and GATA-3 are explored by translating combinatorial logic expressions into differential equations for BCL11B production rate.

RESULTS

Our analysis reveals that only 3 of 32 possible configurations, where GATA-3 works as a dimer, are able to explain not only the time delay, but very importantly, also give rise to irreversibility. The winning models explain the data within the 95% confidence region and are consistent with regard to decay rates.

CONCLUSIONS

This first generation model for early T-cell specification has relatively few players. Yet it explains the gradual transition into a committed state with no return. Encoding logics in a rate equation setting allows determination of binding properties beyond what is possible in a Boolean network.