Now showing items 1-20 of 1153

    • Indigenous Arabs have an intermediate frequency of a Neanderthal-derived COVID-19 risk haplotype compared with other world populations.

      Mineta, Katsuhiko; Goto, Kosuke; Gojobori, Takashi; Alkuraya, Fowzan S. (Clinical genetics, Wiley, 2020-11-27) [Article]
      SARS-CoV-2 has been identified as the cause of an ongoing pandemic (COVID-19) that has infected more than 25 m individuals and caused more than 1 m deaths worldwide (WHO). The highly variable clinical course despite a relatively stable viral genome strongly implicates host factors, including genetics. Mendelian large effect variants have recently been identified although these likely account for a very small number of cases.1 On the other hand, the contribution of several common variants has been demonstrated,2 particularly one locus on chr3 which was identified in the first major GWAS on genetic predisposition to severe COVID19.3 Interestingly, a very recent study has convincingly shown that the risk haplotype in the chr3 locus was introgressed into modern humans from Neanderthal.4 The distribution of this risk haplotype was estimated for a wide range of human populations although Middle Eastern Arabs were missing.4 Here, we calculate the distribution of the risk haplotype in Arabia and discuss that in the context of the overall Neanderthal ancestry in the local population. Representative samples from the major indigenous tribes in Arabia were chosen for analysis with informed consent and genotyped as described in detail elsewhere (Mineta et al, 2020).5 We first confirmed by Haploview that the 13 SNPs that constitute the risk haplotype are in complete LD in indigenous Arabs using previously published WGS data. We then tested the frequency of rs13078854 in 953 samples representing the 28 major indigenous tribes in Arabia. The overall risk allele frequency was 8.6% with 135 heterozygotes and 14 homozygotes (of note, homozygotes had only been documented among South Asians [~10%] and 1 individual in Colombia). As shown in Figure 1, the distribution was largely similar between the different regions.
    • Recessive, Deleterious Variants in SMG8 Expand the Role of Nonsense-Mediated Decay in Developmental Disorders in Humans.

      AlZahrani, Fatema; Kuwahara, Hiroyuki; Long, Yongkang; Al-Owain, Mohammed; Tohary, Mohamed; AlSayed, Moeenaldeen; Mahnashi, Mohammed; Fathi, Lana; Alnemer, Maha; Al-Hamed, Mohamed H; Lemire, Gabrielle; Boycott, Kym M; Hashem, Mais; Han, Wenkai; Al-Maawali, Almundher; Al Mahrizi, Feisal; Al-Thihli, Khalid; Gao, Xin; Alkuraya, Fowzan S (American journal of human genetics, Elsevier BV, 2020-11-25) [Article]
      We have previously described a heart-, eye-, and brain-malformation syndrome caused by homozygous loss-of-function variants in SMG9, which encodes a critical component of the nonsense-mediated decay (NMD) machinery. Here, we describe four consanguineous families with four different likely deleterious homozygous variants in SMG8, encoding a binding partner of SMG9. The observed phenotype greatly resembles that linked to SMG9 and comprises severe global developmental delay, microcephaly, facial dysmorphism, and variable congenital heart and eye malformations. RNA-seq analysis revealed a general increase in mRNA expression levels with significant overrepresentation of core NMD substrates. We also identified increased phosphorylation of UPF1, a key SMG1-dependent step in NMD, which most likely represents the loss of SMG8--mediated inhibition of SMG1 kinase activity. Our data show that SMG8 and SMG9 deficiency results in overlapping developmental disorders that most likely converge mechanistically on impaired NMD.
    • A single neuron subset governs a single coactive neuron circuit in Hydra vulgaris , representing a prototypic feature of neural evolution

      Noro, Yukihiko; Shimizu, Hiroshi; Mineta, Katsuhiko; Gojobori, Takashi (Cold Spring Harbor Laboratory, 2020-11-23) [Preprint]
      The last common ancestor of Bilateria and Cnidaria is believed to be one of the first animals to develop a nervous system over 500 million years ago. Many of the genes involved in the neural function of the advanced nervous system in Bilateria are well conserved in Cnidaria. Thus, Cnidarian representative species, Hydra, is considered to be a living fossil and a good model organism for the study of the putative primitive nervous system in its last common ancestor. The diffuse nervous system of Hydra consists of several peptidergic neuron subsets. However, the specific functions of these subsets remain unclear. Using calcium imaging, here we show that the neuron subsets that express neuropeptide, Hym-176 function as motor neurons to evoke longitudinal contraction. We found that all neurons in a subset defined by the Hym-176 gene (Hym-176A) or its paralogs (Hym-176B) expression are excited simultaneously, which is then followed by longitudinal contraction. This indicates not only that these neuron subsets are motor neurons but also that a single molecularly defined neuron subset forms a single coactive motor circuit. This is in contrast with the Bilaterian nervous system, where a single molecularly defined neuron subset harbors multiple coactive circuits, showing a mixture of neurons firing with different timings. Furthermore, we found that the two motor circuits, one expressing Hym-176B in the body column and the other expressing Hym-176A in the foot, are coordinately regulated to exert region-specific contraction. Our results demonstrate that one neuron subset is likely to form a monofunctional circuit as a minimum functional unit to build a more complex behavior in Hydra. We propose that this simple feature (one subset, one circuit, one function) found in Hydra is a fundamental trait of the primitive nervous system.
    • DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier

      Kulmanov, Maxat; Hoehndorf, Robert (PLOS Computational Biology, Public Library of Science (PLoS), 2020-11-18) [Article]
      Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted in a large number of genotype–phenotype association being available for humans and model organisms. Combined with recent advances in machine learning, it may now be possible to predict human phenotypes resulting from particular molecular aberrations. We developed DeepPheno, a neural network based hierarchical multi-class multi-label classification method for predicting the phenotypes resulting from loss-of-function in single genes. DeepPheno uses the functional annotations with gene products to predict the phenotypes resulting from a loss-of-function; additionally, we employ a two-step procedure in which we predict these functions first and then predict phenotypes. Prediction of phenotypes is ontology-based and we propose a novel ontology-based classifier suitable for very large hierarchical classification tasks. These methods allow us to predict phenotypes associated with any known protein-coding gene. We evaluate our approach using evaluation metrics established by the CAFA challenge and compare with top performing CAFA2 methods as well as several state of the art phenotype prediction approaches, demonstrating the improvement of DeepPheno over established methods. Furthermore, we show that predictions generated by DeepPheno are applicable to predicting gene–disease associations based on comparing phenotypes, and that a large number of new predictions made by DeepPheno have recently been added as phenotype databases.
    • PATHcre8: A Tool That Facilitates the Searching for Heterologous Biosynthetic Routes

      Motwalli, Olaa Amin; Uludag, Mahmut; Mijakovic, Ivan; Alazmi, Meshari; Bajic, Vladimir B.; Gojobori, Takashi; Gao, Xin; Essack, Magbubah (ACS Synthetic Biology, American Chemical Society (ACS), 2020-11-16) [Article]
      Developing computational tools that can facilitate the rational design of cell factories producing desired products at increased yields is challenging, as the tool needs to take into account that the preferred host organism usually has compounds that are consumed by competing reactions that reduce the yield of the desired product. On the other hand, the preferred host organisms may not have the native metabolic reactions needed to produce the compound of interest; thus, the computational tool needs to identify the metabolic reactions that will most efficiently produce the desired product. In this regard, we developed the generic tool PATHcre8 to facilitate an optimized search for heterologous biosynthetic pathway routes. PATHcre8 finds and ranks biosynthesis routes in a large number of organisms, including Cyanobacteria. The tool ranks the pathways based on feature scores that reflect reaction thermodynamics, the potentially toxic products in the pathway (compound toxicity), intermediate products in the pathway consumed by competing reactions (product consumption), and host-specific information such as enzyme copy number. A comparison with several other similar tools shows that PATHcre8 is more efficient in ranking functional pathways. To illustrate the effectiveness of PATHcre8, we further provide case studies focused on isoprene production and the biodegradation of cocaine. PATHcre8 is free for academic and nonprofit users and can be accessed at https://www.cbrc.kaust.edu.sa/pathcre8/.
    • A nanobody-functionalized organic electrochemical transistor for the rapid detection of SARS-CoV-2 or MERS antigens at the physical limit

      Guo, Keying; Wustoni, Shofarul; Koklu, Anil; Díaz-Galicia, Escarlet; Moser, Maximilian; Hama, Adel; Alqahtani, Ahmed A.; Nazir Ahmad, Adeel; Alhamlan, Fatimah Saeed; McCulloch, Iain; Arold, Stefan T.; Grunberg, Raik; Inal, Sahika (Cold Spring Harbor Laboratory, 2020-11-13) [Preprint]
      The COVID-19 pandemic highlights the need for rapid protein detection and quantification at the single-molecule level in a format that is simple and robust enough for widespread point-of-care applications. We here introduce a modular nanobody-organic electrochemical transistor architecture that enables the fast and specific detection and quantification of single-molecule to nanomolar protein antigen concentrations in complex bodily fluids. The sensor combines a new solution-processable organic semiconductor material in the transistor channel with the high-density and orientation-controlled bioconjugation of nanobody fusion proteins on disposable gate electrodes. It provides results after a 10 minutes exposure to 5 μL of unprocessed samples, maintains high specificity and single-molecule sensitivity in human saliva or serum, and is rapidly reprogrammed towards any protein target for which nanobodies exist. We demonstrate the use of this highly modular platform for the detection of green fluorescent protein, SARS-CoV-1/2, and MERS-CoV spike proteins and validate the sensor for COVID-19 screening in unprocessed clinical nasopharyngeal swab and saliva samples.
    • A nanobody-functionalized organic electrochemical transistor for the rapid detection of SARS-CoV-2 or MERS antigens at the physical limit

      Guo, Keying; Wustoni, Shofarul; Koklu, Anil; Díaz-Galicia, Escarlet; Moser, Maximilian; Hama, Adel; Alqahtani, Ahmed A.; Nazir Ahmad, Adeel; Alhamlan, Fatimah Saeed; McCulloch, Iain; Arold, Stefan T.; Grunberg, Raik; Inal, Sahika (Cold Spring Harbor Laboratory, 2020-11-13) [Preprint]
      The COVID-19 pandemic highlights the need for rapid protein detection and quantification at the single-molecule level in a format that is simple and robust enough for widespread point-of-care applications. We here introduce a modular nanobody-organic electrochemical transistor architecture that enables the fast and specific detection and quantification of single-molecule to nanomolar protein antigen concentrations in complex bodily fluids. The sensor combines a new solution-processable organic semiconductor material in the transistor channel with the high-density and orientation-controlled bioconjugation of nanobody fusion proteins on disposable gate electrodes. It provides results after a 10 minutes exposure to 5 μL of unprocessed samples, maintains high specificity and single-molecule sensitivity in human saliva or serum, and is rapidly reprogrammed towards any protein target for which nanobodies exist. We demonstrate the use of this highly modular platform for the detection of green fluorescent protein, SARS-CoV-1/2, and MERS-CoV spike proteins and validate the sensor for COVID-19 screening in unprocessed clinical nasopharyngeal swab and saliva samples.
    • Succinic semialdehyde dehydrogenase deficiency presenting with central hypothyroidism

      Alghamdi, Malak; Alkhamis, Waleed H.; Jamjoom, Dima Z.; Al Khalifah, Reem; Alshammari, Nawaf Rahi; Alsumaili, Khalid; Arold, Stefan T. (Clinical Case Reports, Wiley, 2020-11-11) [Article]
      Central hypothyroidism might be another clinical sign of SSADH deficiency which prompts urinary organic acid screening for GHB in central hypothyroidism patients. Studies on GABA and thyroid hormone interaction might be a concept of a new therapy.
    • Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms

      Li, Ran; Yu, Liangyong; Zhou, Bo; Zeng, Xiangrui; Wang, Zhenyu; Yang, Xiaoyan; Zhang, Jing; Gao, Xin; Jiang, Rui; Xu, Min (PLOS Computational Biology, Public Library of Science (PLoS), 2020-11-11) [Article]
      Cryo-electron tomography (cryo-ET) provides 3D visualization of subcellular components in the near-native state and at sub-molecular resolutions in single cells, demonstrating an increasingly important role in structural biology in situ. However, systematic recognition and recovery of macromolecular structures in cryo-ET data remain challenging as a result of low signal-to-noise ratio (SNR), small sizes of macromolecules, and high complexity of the cellular environment. Subtomogram structural classification is an essential step for such task. Although acquisition of large amounts of subtomograms is no longer an obstacle due to advances in automation of data collection, obtaining the same number of structural labels is both computation and labor intensive. On the other hand, existing deep learning based supervised classification approaches are highly demanding on labeled data and have limited ability to learn about new structures rapidly from data containing very few labels of such new structures. In this work, we propose a novel approach for subtomogram classification based on few-shot learning. With our approach, classification of unseen structures in the training data can be conducted given few labeled samples in test data through instance embedding. Experiments were performed on both simulated and real datasets. Our experimental results show that we can make inference on new structures given only five labeled samples for each class with a competitive accuracy (> 0.86 on the simulated dataset with SNR = 0.1), or even one sample with an accuracy of 0.7644. The results on real datasets are also promising with accuracy > 0.9 on both conditions and even up to 1 on one of the real datasets. Our approach achieves significant improvement compared with the baseline method and has strong capabilities of generalizing to other cellular components.
    • “What Doesn’t Kill You Makes You Stronger”: Future Applications of Amyloid Aggregates in Biomedicine

      Abdelrahman, Sherin; Alghrably, Mawadda; Lachowicz, Joanna Izabela; Emwas, Abdul-Hamid M.; Hauser, Charlotte; Jaremko, Mariusz (Molecules, MDPI AG, 2020-11-11) [Article]
      Amyloid proteins are linked to the pathogenesis of several diseases including Alzheimer’s disease, but at the same time a range of functional amyloids are physiologically important in humans. Although the disease pathogenies have been associated with protein aggregation, the mechanisms and factors that lead to protein aggregation are not completely understood. Paradoxically, unique characteristics of amyloids provide new opportunities for engineering innovative materials with biomedical applications. In this review, we discuss not only outstanding advances in biomedical applications of amyloid peptides, but also the mechanism of amyloid aggregation, factors affecting the process, and core sequences driving the aggregation. We aim with this review to provide a useful manual for those who engineer amyloids for innovative medicine solutions.
    • Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species

      Zheng, Yumin; Wang, Haohan; Zhang, Yang; Gao, Xin; Xing, Eric P.; Xu, Min (PLOS Computational Biology, Public Library of Science (PLoS), 2020-11-05) [Article]
      In eukaryotes, polyadenylation (poly(A)) is an essential process during mRNA maturation. Identifying the cis-determinants of poly(A) signal (PAS) on the DNA sequence is the key to understand the mechanism of translation regulation and mRNA metabolism. Although machine learning methods were widely used in computationally identifying PAS, the need for tremendous amounts of annotation data hinder applications of existing methods in species without experimental data on PAS. Therefore, cross-species PAS identification, which enables the possibility to predict PAS from untrained species, naturally becomes a promising direction. In our works, we propose a novel deep learning method named Poly(A)-DG for cross-species PAS identification. Poly(A)-DG consists of a Convolution Neural Network-Multilayer Perceptron (CNN-MLP) network and a domain generalization technique. It learns PAS patterns from the training species and identifies PAS in target species without re-training. To test our method, we use three species and build cross-species training sets with two of them and evaluate the performance of the remaining one. Moreover, we test our method against insufficient data and imbalanced data issues and demonstrate that Poly(A)-DG not only outperforms state-of-the-art methods but also maintains relatively high accuracy when it comes to a smaller or imbalanced training set.
    • Cover Image: Novel tumour suppressor roles for GZMA and RASGRP1 in Theileria annulata-transformed macrophages and human B lymphoma cells (Cellular Microbiology 12/2020)

      Rchiad, ‍Zineb; Haidar, Malak; Ansari, Hifzur Rahman; Tajeri, Shahin; Mfarrej, Sara; Ben Rached, Fathia; Kaushik, Abhinav; Langsley, Gordon; Pain, Arnab (Cellular Microbiology, Wiley, 2020-11-05) [Article]
      Theileria annulata is a tick-transmitted apicomplexan parasite that infects and transforms bovine leukocytes into disseminating tumours that cause a disease called tropical theileriosis. Using comparative transcriptomics we identified genes transcriptionally perturbed during Theileria-induced leukocyte transformation. Dataset comparisons highlighted a small set of genes associated with Theileria-transformed leukocyte dissemination. The roles of Granzyme A (GZMA) and RAS guanyl-releasing protein 1 (RASGRP1) were verified by CRISPR/Cas9-mediated knockdown. Knocking down expression of GZMA and RASGRP1 in attenuated macrophages led to a regain in their dissemination in Rag2/γC mice confirming their role as dissemination suppressors in vivo. We further evaluated the roles of GZMA and RASGRP1 in human B lymphomas by comparing the transcriptome of 934 human cancer cell lines to that of Theileria-transformed bovine host cells. We confirmed dampened dissemination potential of human B lymphomas that overexpress GZMA and RASGRP1. Our results provide evidence that GZMA and RASGRP1 have a novel tumour suppressor function in both T. annulata-infected bovine host leukocytes and in human B lymphomas.
    • Exponential increase of plastic burial in mangrove sediments as a major plastic sink

      Martin, Cecilia; Baalkhuyur, F.; Valluzzi, L.; Saderne, Vincent; Cusack, Michael; Almahasheer, Hanan; Rabaoui, Lotfi; Rabaoui, L.; Qurban, M.A.; Arias-Ortiz, Ariane; Masqué, Pere; Duarte, Carlos M. (Science Advances, American Association for the Advancement of Science (AAAS), 2020-10-28) [Article]
      Sequestration of plastics in sediments is considered the ultimate sink of marine plastic pollution that would justify unexpectedly low loads found in surface waters. Here, we demonstrate that mangroves, generally supporting high sediment accretion rates, efficiently sequester plastics in their sediments. To this end, we extracted microplastics from dated sediment cores of the Red Sea and Arabian Gulf mangrove (Avicennia marina) forests along the Saudi Arabian coast. We found that microplastics <0.5 mm dominated in mangrove sediments, helping explain their scarcity, in surface waters. We estimate that 50 ± 30 and 110 ± 80 metric tons of plastic may have been buried since the 1930s in mangrove sediments across the Red Sea and the Arabian Gulf, respectively. We observed an exponential increase in the plastic burial rate (8.5 ± 1.2% year$^{−1}$) since the 1950s in line with the global plastic production increase, confirming mangrove sediments as long-term sinks for plastics.
    • The Small Giant Clam, Tridacna maxima Exhibits Minimal Population Genetic Structure in the Red Sea and Genetic Differentiation From the Gulf of Aden

      Lim, Kah Kheng; Rossbach, Susann; Geraldi, Nathan; Schmidt-Roach, Sebastian; Serrão, Ester A.; Duarte, Carlos M. (Frontiers in Marine Science, Frontiers Media SA, 2020-10-22) [Article]
      The Red Sea serves as a natural laboratory to investigate mechanisms of genetic differentiation and population dynamics of reef organisms due to its high species endemism. Giant clams, important yet understudied coral reef engineering species, are ideal candidates for such study in this region. This paper presents the first population genetics study of giant clams covering the entire East coast of the Red Sea. Our study aimed to investigate the population structure of the small giant clam, Tridacna maxima, based on 501-bp fragment of the cytochrome c oxidase I gene from 194 individuals (126 new sequences from this study plus 68 sequences from GenBank), collected from 14 locations in the Red Sea and Gulf of Aden (RSGA). For the genetic analysis, each sampling site was treated as a population. T. maxima showed high genetic diversity, with high gene flow in almost all sampling sites. The insignificant global ϕST-value of 0.02 (p > 0.05) suggests the presence of one large, panmictic population across a wide range of temperature and salinity gradients in the RSGA. Despite this, the population in Djibouti was genetically differentiated from the other 11 populations in the Red Sea, suggesting a connectivity break between the Red Sea and the Gulf of Aden. These results could be explained by the oceanographic features facilitating wide larval transport inside the Red Sea, and creating a dispersal barrier to the Gulf of Aden. Besides larval dispersal by currents, apparent successful establishment following dispersal is probably facilitated by the mode and time of reproduction as well as the ability of T. maxima to achieve high fitness in the highly variable environmental conditions of the Red Sea.
    • Fractional-order Modeling of the Arterial Compliance: An Alternative Surrogate Measure of the Arterial Stiffness

      Bahloul, Mohamed; Laleg-Kirati, Taous-Meriem (arXiv, 2020-10-20) [Preprint]
      Recent studies have demonstrated the advantages of fractional-order calculus tools for probing the viscoelastic properties of collagenous tissue, characterizing the arterial blood flow and red cell membrane mechanics, and modeling the aortic valve cusp. In this article, we present a novel lumped-parameter equivalent circuit models of the apparent arterial compliance using a fractional-order capacitor (FOC). FOC, which generalizes capacitors and resistors, displays a fractional-order behavior that can capture both elastic and viscous properties through a power-law formulation. The proposed framework describes the dynamic relationship between the blood pressure input and blood volume, using linear fractional-order differential equations. The results show that the proposed models present reasonable fit performance with in-silico data of more than 4,000 subjects. Additionally, strong correlations have been identified between the fractional-order parameter estimates and the central hemodynamic determinants as well as pulse wave velocity indexes. Therefore, fractional-order based paradigm of arterial compliance shows prominent potential as an alternative tool in the analysis of arterial stiffness.
    • RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads.

      Liao, Xingyu; Gao, Xin; Zhang, Xiankai; Wu, Fang-Xiang; Wang, Jianxin (BMC bioinformatics, Springer Science and Business Media LLC, 2020-10-19) [Article]
      BACKGROUND:Repetitive sequences account for a large proportion of eukaryotes genomes. Identification of repetitive sequences plays a significant role in many applications, such as structural variation detection and genome assembly. Many existing de novo repeat identification pipelines or tools make use of assembly of the high-frequency k-mers to obtain repeats. However, a certain degree of sequence coverage is required for assemblers to get the desired assemblies. On the other hand, assemblers cut the reads into shorter k-mers for assembly, which may destroy the structure of the repetitive regions. For the above reasons, it is difficult to obtain complete and accurate repetitive regions in the genome by using existing tools. RESULTS:In this study, we present a new method called RepAHR for de novo repeat identification by assembly of the high-frequency reads. Firstly, RepAHR scans next-generation sequencing (NGS) reads to find the high-frequency k-mers. Secondly, RepAHR filters the high-frequency reads from whole NGS reads according to certain rules based on the high-frequency k-mer. Finally, the high-frequency reads are assembled to generate repeats by using SPAdes, which is considered as an outstanding genome assembler with NGS sequences. CONLUSIONS:We test RepAHR on five data sets, and the experimental results show that RepAHR outperforms RepARK and REPdenovo for detecting repeats in terms of N50, reference alignment ratio, coverage ratio of reference, mask ratio of Repbase and some other metrics.
    • Stress concentration analysis and fabrication of silicon (100) based ultra-stretchable structures with parylene coating

      Rehman, Mutee Ur; Babatain, Wedyan; Shaikh, Sohail F.; Conchouso Gonzalez, David; Qaiser, Nadeem; Hussain, Muhammad Mustafa; Rojas, Jhonathan Prieto (Extreme Mechanics Letters, Elsevier BV, 2020-10-19) [Article]
      Research in stretchable electronics is helping to revolutionize the current electronic industry, particularly in wearable and bio-integrated devices. Cost-effectiveness and easy manufacturing are key factors that contribute to shaping the fate of such technologies. In this work, we present a fabrication method for a novel ultra-stretchable, serpentine-arm spiral (SAS) that was built using a low-cost, standard bulk silicon (100) wafer. However, structural defects that often appear during patterning processes, can lead to stress concentration and structural failure at these sites upon stretching. Parylene coating of the structures is proposed to minimize this stress concentration and improve structure's robustness. Finite element analysis (FEA) was performed to demonstrate the concentration of stress at these defective sites with 2 sizes (0.1μm and 1μm) and at different locations along the arms. Results show that SAS structures reach up to ∼80% stress reduction at the defective location compared to straight-arm spirals, while the parylene-coating helps to reduce it up to ∼60% further. On the other hand, fabricated uncoated, SAS structures reached up to ∼600% prescribed strain before fracture, while parylene-coating improves this maximum admissible strain in ∼50%. Additionally, a cyclic tensile test was then performed on the fabricated structures, uncoated and parylene-coated, for over 3000 cycles without fracture. The results observed on coated structures greatly improve the mechanical reliance of such brittle structures, which could be extended to other stretchable configurations.
    • Understanding High-Salt and Cold Adaptation of a Polyextremophilic Enzyme

      Karan, Ram; Mathew, Sam; Muhammad, Reyhan; Bautista, Didier B.; Vogler, Malvina M.; Eppinger, Jörg; Oliva, Romina; Cavallo, Luigi; Arold, Stefan T.; Rueping, Magnus (Microorganisms, MDPI AG, 2020-10-16) [Article]
      The haloarchaeon Halorubrum lacusprofundi is among the few polyextremophilic organisms capable of surviving in one of the most extreme aquatic environments on Earth, the Deep Lake of Antarctica (−18 °C to +11.5 °C and 21–28%, w/v salt content). Hence, H. lacusprofundi has been proposed as a model for biotechnology and astrobiology to investigate potential life beyond Earth. To understand the mechanisms that allow proteins to adapt to both salinity and cold, we structurally (including X-ray crystallography and molecular dynamics simulations) and functionally characterized the β-galactosidase from H. lacusprofundi (hla_bga). Recombinant hla_bga (produced in Haloferax volcanii) revealed exceptional stability, tolerating up to 4 M NaCl and up to 20% (v/v) of organic solvents. Despite being cold-adapted, hla_bga was also stable up to 60 °C. Structural analysis showed that hla_bga combined increased surface acidity (associated with halophily) with increased structural flexibility, fine-tuned on a residue level, for sustaining activity at low temperatures. The resulting blend enhanced structural flexibility at low temperatures but also limited protein movements at higher temperatures relative to mesophilic homologs. Collectively, these observations help in understanding the molecular basis of a dual psychrophilic and halophilic adaptation and suggest that such enzymes may be intrinsically stable and functional over an exceptionally large temperature range.
    • Interleukin-26 activates macrophages and facilitates killing of Mycobacterium tuberculosis

      Hawerkamp, Heike C.; van Geelen, Lasse; Korte, Jan; Di Domizio, Jeremy; Swidergall, Marc; Momin, Afaque Ahmad Imtiyaz; Guzmán-Vega, Francisco J.; Arold, Stefan T.; Ernst, Joachim; Gilliet, Michel; Kalscheuer, Rainer; Homey, Bernhard; Meller, Stephan (Scientific Reports, Springer Science and Business Media LLC, 2020-10-14) [Article]
      Abstract Tuberculosis-causing Mycobacterium tuberculosis (Mtb) is transmitted via airborne droplets followed by a primary infection of macrophages and dendritic cells. During the activation of host defence mechanisms also neutrophils and T helper 1 (TH1) and TH17 cells are recruited to the site of infection. The TH17 cell-derived interleukin (IL)-17 in turn induces the cathelicidin LL37 which shows direct antimycobacterial effects. Here, we investigated the role of IL-26, a TH1- and TH17-associated cytokine that exhibits antimicrobial activity. We found that both IL-26 mRNA and protein are strongly increased in tuberculous lymph nodes. Furthermore, IL-26 is able to directly kill Mtb and decrease the infection rate in macrophages. Binding of IL-26 to lipoarabinomannan might be one important mechanism in extracellular killing of Mtb. Macrophages and dendritic cells respond to IL-26 with secretion of tumor necrosis factor (TNF)-α and chemokines such as CCL20, CXCL2 and CXCL8. In dendritic cells but not in macrophages cytokine induction by IL-26 is partly mediated via Toll like receptor (TLR) 2. Taken together, IL-26 strengthens the defense against Mtb in two ways: firstly, directly due to its antimycobacterial properties and secondly indirectly by activating innate immune mechanisms.
    • Predicting Candidate Genes From Phenotypes, Functions, And Anatomical Site Of Expression.

      Chen, Jun; Althagafi, Azza Th.; Hoehndorf, Robert (Bioinformatics (Oxford, England), Oxford University Press (OUP), 2020-10-14) [Article]
      MOTIVATION:Over the past years, many computational methods have been developed to incorporate information about phenotypes for disease gene prioritization task. These methods generally compute the similarity between a patient's phenotypes and a database of gene-phenotype to find the most phenotypically similar match. The main limitation in these methods is their reliance on knowledge about phenotypes associated with particular genes, which is not complete in humans as well as in many model organisms such as the mouse and fish. Information about functions of gene products and anatomical site of gene expression is available for more genes and can also be related to phenotypes through ontologies and machine learning models. RESULTS:We developed a novel graph-based machine learning method for biomedical ontologies which is able to exploit axioms in ontologies and other graph-structured data. Using our machine learning method, we embed genes based on their associated phenotypes, functions of the gene products, and anatomical location of gene expression. We then develop a machine learning model to predict gene-disease associations based on the associations between genes and multiple biomedical ontologies, and this model significantly improves over state of the art methods. Furthermore, we extend phenotype-based gene prioritization methods significantly to all genes which are associated with phenotypes, functions, or site of expression. AVAILABILITY:Software and data are available at https://github.com/bio-ontology-research-group/DL2Vec.