As the infection of 2019-nCoV coronavirus is quickly developing into a global pneumonia epidemic, the careful analysis of its transmission and cellular mechanisms is sorely needed. In this Communication, we first analyzed two recent studies that concluded that snakes are the intermediate hosts of 2019-nCoV and that the 2019-nCoV spike protein insertions share a unique similarity to HIV-1. However, the reimplementation of the analyses, built on larger scale data sets using state-of-theart bioinformatics methods and databases, presents clear evidence that rebuts these conclusions. Next, using metagenomic samples from Manis javanica, we assembled a draft genome of the 2019-nCoV-like coronavirus, which shows 73% coverage and 91% sequence identity to the 2019-nCoV genome. In particular, the alignments of the spike surface glycoprotein receptor binding domain revealed four times more variations in the bat coronavirus RaTG13 than in the Manis coronavirus compared with 2019-nCoV, suggesting the pangolin as a missing link in the transmission of 2019-nCoV from bats to human.

Most proteins exist with multiple domains in cells for cooperative functionality. However, structural biology and protein folding methods are often optimized for single-domain structures, resulting in a rapidly growing gap between the improved capability for tertiary structure determination and high demand for multidomain structure models. We have developed a pipeline, termed DEMO, for constructing multidomain protein structures by docking-based domain assembly simulations, with interdomain orientations determined by the distance profiles from analogous templates as detected through domain-level structure alignments. The pipeline was tested on a comprehensive benchmark set of 356 proteins consisting of 2–7 continuous and discontinuous domains, for which DEMO generated models with correct global fold (TM-score > 0.5) for 86% of cases with continuous domains and for 100% of cases with discontinuous domain structures, starting from randomly oriented target-domain structures. DEMO was also applied to reassemble multidomain targets in the CASP12 and CASP13 experiments using domain structures excised from the top server predictions, where the full-length DEMO models showed a significantly improved quality over the original server models. Finally, sparse restraints of mass spectrometry-generated cross-linking data and cryo-EM density maps are incorporated into DEMO, resulting in improvements in the average TM-score by 6.3% and 12.5%, respectively. The results demonstrate an efficient approach to assembling multidomain structures, which can be easily used for automated, genome-scale multidomain protein structure assembly.

We hypothesized that a decreased susceptibility to the development of hypocapnic central apnea during non-rapid eye movement (NREM) sleep in women compared with men could be an explanation for the gender difference in the sleep apnea/hypopnea syndrome. We studied eight men (age 25-35 yr) and eight women in the midluteal phase of the menstrual cycle (age 21-43 yr); we repeated studies in six women during the midfollicular phase. Hypocapnia was induced via nasal mechanical ventilation for 3 min, with respiratory frequency matched to eupneic frequency. Tidal volume (VT) was increased between 110 and 200% of eupneic control. Cessation of mechanical ventilation resulted in hypocapnic central apnea or hypopnea, depending on the magnitude of hypocapnia. Nadir minute ventilation in the recovery period was plotted against the change in end-tidal PCO(2) (PET(CO(2))) per trial; minute ventilation was given a value of 0 during central apnea. The apneic threshold was defined as the x-intercept of the linear regression line. In women, induction of a central apnea required an increase in VT to 155 +/- 29% (mean +/- SD) and a reduction of PET(CO(2)) by -4.72 +/- 0.57 Torr. In men, induction of a central apnea required an increase in VT to 142 +/- 13% and a reduction of PET(CO(2)) by -3.54 +/- 0.31 Torr (P = 0.002). There was no difference in the apneic threshold between the follicular and the luteal phase in women. Premenopausal women are less susceptible to hypocapnic disfacilitation during NREM sleep than men. This effect was not explained by progesterone. Preservation of ventilatory motor output during hypocapnia may explain the gender difference in sleep apnea.

Motivation Protein domains are subunits that can fold and function independently. Correct domain boundary assignment is thus a critical step toward accurate protein structure and function analyses. There is, however, no efficient algorithm available for accurate domain prediction from sequence. The problem is particularly challenging for proteins with discontinuous domains, which consist of domain segments that are separated along the sequence. Results We developed a new algorithm, FUpred, which predicts protein domain boundaries utilizing contact maps created by deep residual neural networks coupled with coevolutionary precision matrices. The core idea of the algorithm is to retrieve domain boundary locations by maximizing the number of intra-domain contacts, while minimizing the number of inter-domain contacts from the contact maps. FUpred was tested on a large-scale dataset consisting of 2549 proteins and generated correct single- and multi-domain classifications with a Matthew’s correlation coefficient of 0.799, which was 19.1% (or 5.3%) higher than the best machine learning (or threading)-based method. For proteins with discontinuous domains, the domain boundary detection and normalized domain overlapping scores of FUpred were 0.788 and 0.521, respectively, which were 17.3% and 23.8% higher than the best control method. The results demonstrate a new avenue to accurately detect domain composition from sequence alone, especially for discontinuous, multi-domain proteins. Availability and implementation https://zhanglab.ccmb.med.umich.edu/FUpred. Supplementary information Supplementary data are available at Bioinformatics online.

The hypocapnic apneic threshold (AT) is lower in women relative to men. To test the hypothesis that the gender difference in AT was due to testosterone, we determined the AT during non-rapid eye movement sleep in eight healthy, nonsnoring, premenopausal women before and after 10-12 days of transdermal testosterone. Hypocapnia was induced via nasal mechanical ventilation (MV) for 3 min with tidal volumes ranging from 175 to 215% above eupneic tidal volume and respiratory frequency matched to eupneic frequency. Cessation of MV resulted in hypocapnic central apnea or hypopnea depending on the magnitude of hypocapnia. Nadir minute ventilation as a percentage of control (%Ve) was plotted against the change in end-tidal CO(2) (Pet(CO(2))); %Ve was given a value of zero during central apnea. The AT was defined as the Pet(CO(2)) at which the apnea closest to the last hypopnea occurred; hypocapnic ventilatory response (HPVR) was defined as the slope of the linear regression Ve vs. Pet(CO(2)). Both the AT (39.5 +/- 2.9 vs. 42.1 +/- 3.0 Torr; P = 0.002) and HPVR (0.20 +/- 0.05 vs. 0.33 +/- 0.11%Ve/Torr; P = 0.016) increased with testosterone administration. We conclude that testosterone administration increases AT in premenopausal women, suggesting that the increased breathing instability during sleep in men is related to the presence of testosterone.

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The topology of protein folds can be specified by the inter-residue contact-maps and accurate contact-map prediction can help ab initio structure folding. We developed TripletRes to deduce protein contact-maps from discretized distance profiles by end-to-end training of deep residual neural-networks. Compared to previous approaches, the major advantage of TripletRes is in its ability to learn and directly fuse a triplet of coevolutionary matrices extracted from the whole-genome and metagenome databases and therefore minimize the information loss during the course of contact model training. TripletRes was tested on a large set of 245 non-homologous proteins from CASP 11&12 and CAMEO experiments and outperformed other top methods from CASP12 by at least 58.4% for the CASP 11&12 targets and 44.4% for the CAMEO targets in the top-L long-range contact precision. On the 31 FM targets from the latest CASP13 challenge, TripletRes achieved the highest precision (71.6%) for the top-L/5 long-range contact predictions. It was also shown that a simple re-training of the TripletRes model with more proteins can lead to further improvement with precisions comparable to state-of-the-art methods developed after CASP13. These results demonstrate a novel efficient approach to extend the power of deep convolutional networks for high-accuracy medium- and long-range protein contact-map predictions starting from primary sequences, which are critical for constructing 3D structure of proteins that lack homologous templates in the PDB library.

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