Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations.

Human genome sequencing studies have identified numerous loci associated with complex diseases. However, translating human genetic and genomic findings to disease pathobiology and therapeutic discovery remains a major challenge at multiscale interactome network levels. Here, we present a deep-learning-based ensemble framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that accurately predicts protein binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms, generating comprehensive structurally-informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods. We further systematically validated PIONEER predictions experimentally through generating 2,395 mutations and testing their impact on 6,754 mutation-interaction pairs, confirming the high quality and validity of PIONEER predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces after mapping mutations from ~60,000 germline exomes and ~36,000 somatic genomes. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from pan-cancer analysis of ~11,000 tumor whole-exomes across 33 cancer types. We show that PIONEER-predicted oncoPPIs are significantly associated with patient survival and drug responses from both cancer cell lines and patient-derived xenograft mouse models. We identify a landscape of PPI-perturbing tumor alleles upon ubiquitination by E3 ligases, and we experimentally validate the tumorigenic KEAP1-NRF2 interface mutation p.Thr80Lys in non-small cell lung cancer. We show that PIONEER-predicted PPI-perturbing alleles alter protein abundance and correlates with drug responses and patient survival in colon and uterine cancers as demonstrated by proteogenomic data from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

Adsorption Behavior of Diclofenac on Polystyrene and Poly(butylene adipate-co-terephthalate) Microplastics: Influencing Factors and Adsorption Mechanism.

To unveil the intricacies surrounding the interaction between microplastics (MPs) and pollutants, diligent investigation is warranted to mitigate the environmental perils they pose. This exposition delves into the sorption behavior and mechanism of diclofenac sodium (DCF), a contaminant, upon two distinct materials: polystyrene (PS) and poly(butylene adipate-co-terephthalate) (PBAT). Experimental adsorption endeavors solidify the observation that the adsorption capacity of DCF onto the designated MPs amounts to Q(PBAT) = 9.26 mg g-1 and Q(PS) = 9.03 mg g-1, respectively. An exploration of the factors governing these discrepant adsorption phenomena elucidates the influence of MPs and DCF properties, environmental factors, as well as surfactants. Fitting procedures underscore the suitability of the pseudo-second-order kinetic and Freundlich models in capturing the intricacies of the DCF adsorption process onto MPs, corroborating the notion that the mentioned process is characterized by non-homogeneous chemisorption. Moreover, this inquiry unveils that the primary adsorption mechanisms of DCF upon MPs encompass electrostatic interaction, hydrogen bonding, and halo hydrogen bonding. An additional investigation concerns the impact of commonly encountered surfactants in aqueous environments on the adsorption of DCF onto MPs. The presence of surfactants elicits modifications in the surface charge properties of MPs, consequently influencing their adsorption efficacy vis-à-vis DCF.

Desorption of sulfamethoxazole from polyamide 6 microplastics: Environmental factors, simulated gastrointestinal fluids, and desorption mechanisms.

Microplastics (MPs) can enrich pollutants after being released into the environment, and the contaminants-loaded MPs are usually ingested by organisms, resulting in a potential dual biotoxic effect. In this paper, the adsorption behavior of Sulfamethoxazole (SMX) on Polyamide 6 (PA6) MPs was systematically investigated and simulated by the kinetic and isotherm models. The effect of environmental conditions (pH, salinity) on the adsorption process was studied, and the desorption behavior of SMX-loaded PA6 MPs was focused on simulating the seawater, ultrapure water, gastric and intestinal fluids. We found that lower pH and solubilization of SMX by gastrointestinal components (bovine serum albumin (BSA), sodium taurocholate (NaT), and pepsin) can reduce the electrostatic interaction between the surface charge of PA6 MPs and SMX. The result will lead to an increase in the desorption capacity of SMX-loaded PA6 MPs in gastrointestinal fluids and therefore will provide a reasonable mechanism for the desorption of SMX-loaded PA6 MPs in the gastrointestinal fluids. This study will provide a theoretical reference for studying the desorption behavior of SMX-loaded PA6 MPs under gastrointestinal conditions.

Comparing the adsorption of methyl orange and malachite green on similar yet distinct polyamide microplastics: Uncovering hydrogen bond interactions.

Microplastics (MPs) and dye pollutants are widespread in aquatic environments. Here, the adsorption characteristics of anionic dye methyl orange (MO) and cationic dye malachite green (MG) on polyamide 6 (PA6) and polyamide 66 (PA66) MPs were investigated, including kinetics, isotherm equilibrium and thermodynamics. The co-adsorption of MO and MG under different pH was also evaluated. The results reveal that the adsorption process of MO and MG is suitably expounded by a pseudo-second-order kinetic model. The process can be characterized by two stages: internal diffusion and external diffusion. The isothermal adsorption equilibrium of MO and MG can be effectively described using the Langmuir model, signifying monolayer adsorption. Furthermore, the thermodynamic results indicated that the adsorption was spontaneous with exothermic and endothermic properties, respectively. The results of binary systems reveal that MO dominates the adsorption at low pH (2-5), while MG dominates at high pH (8-10). Strong competitive adsorption was observed between MO and MG in neutral conditions (pH 6-8). The desorption experiments confirm that PA6 and PA66 could serve as potential carriers of MO and MG. The interaction between dyes and polyamide MPs is primarily mediated through hydrogen bonds and electrostatic attraction. The results reveal that PA6 formed more hydrogen bonds with the dyes, resulting in higher adsorption capacity than that of PA66. This difference can be attributed to the disparities in the synthesis process and polymerization method. Our study uncovered the adsorption mechanism of dye pollutants on PA6 and PA66, and provided a more comprehensive theoretical basis for the risk assessment concerning different types of polyamide MPs in aquatic environments.

Phylogenomic analysis, cryptic species discovery, and DNA barcoding of the genus Cibotium in China based on plastome data.

Germplasm resources are the source of herbal medicine production. The cultivation of superior germplasm resources helps to resolve the conflict between long-term population persistence and growing market demand by consistently producing materials with high quality. The fern species Cibotium barometz is the original plant of cibotii rhizoma ("Gouji"), a traditional Chinese medicine used in the therapy of pain, weakness, and numbness in the lower extremities. Long-history medicinal use has caused serious wild population decline in China. Without sufficient understanding of the species and lineage diversity of Cibotium, it is difficult to propose a targeted conservation scheme at present, let alone select high-quality germplasm resources. In order to fill such a knowledge gap, this study sampled C. barometz and relative species throughout their distribution in China, performed genome skimming to obtain plastome data, and conducted phylogenomic analyses. We constructed a well-supported plastome phylogeny of Chinese Cibotium, which showed that three species with significant genetic differences are distributed in China, namely C. barometz, C. cumingii, and C. sino-burmaense sp. nov., a cryptic species endemic to NW Yunnan and adjacent regions of NE Myanmar. Moreover, our results revealed two differentiated lineages of C. barometz distributed on the east and west sides of a classic phylogeographic boundary that was probably shaped by monsoons and landforms. We also evaluated the resolution of nine traditional barcode loci and designed five new DNA barcodes based on the plastome sequence that can distinguish all these species and lineages of Chinese Cibotium accurately. These novel findings on a genetic basis will guide conservation planners and medicinal plant breeders to build systematic conservation plans and exploit the germplasm resources of Cibotium in China.

Implantable QR code subcutaneous microchip using photoacoustic and ultrasound microscopy for secure and convenient individual identification and authentication.

Individual identification and authentication techniques are merged into many aspects of human life with various applications, including access control, payment or banking transfer, and healthcare. Yet conventional identification and authentication methods such as passwords, biometrics, tokens, and smart cards suffer from inconvenience and/or insecurity. Here, inspired by quick response (QR) code and implantable microdevices, implantable and minimally-invasive QR code subcutaneous microchips (QRC-SMs) are proposed to be an effective approach to carry useful and private information, thus enabling individual identification and authentication. Two types of QRC-SMs, QRC-SMs with "hole" and "flat" elements and QRC-SMs with "titanium-coated" and "non-coated" elements, are designed and fabricated to store personal information. Corresponding ultrasound microscopy and photoacoustic microscopy are used for imaging the QR code pattern underneath skin, and open-source artificial intelligence algorithm is applied for QR code detection and recognition. Ex vivo experiments under tissue and in vivo experiments with QRC-SMs implanted in live mice have been performed, demonstrating successful information retrieval from implanted QRC-SMs. QRC-SMs are hidden subcutaneously and invisible to the eyes. They cannot be forgotten, misplaced or lost, and can always be ready for timely medical identification, access control, and payment or banking transfer. Hence, QRC-SMs provide promising routes towards private, secure, and convenient individual identification and authentication.

Miniature Probe for Optomechanical Focus-Adjustable Optical-Resolution Photoacoustic Endoscopy.

Photoacoustic microscopy (PAM) is a promising imaging modality because it is able to reveal optical absorption contrast in high resolution on the order of a micrometer. It can be applied in an endoscopic approach by implementing PAM into a miniature probe, termed photoacoustic endoscopy (PAE). Here we develop a miniature focus-adjustable PAE (FA-PAE) probe characterized by both high resolution (in micrometers) and large depth of focus (DOF) via a novel optomechanical design for focus adjustment. To realize high resolution and large DOF in a miniature probe, a 2-mm plano-convex lens is specially adopted, and the mechanical translation of a single-mode fiber is meticulously designed to allow the use of multi-focus image fusion (MIF) for extended DOF. Compared with existing PAE probes, our FA-PAE probe achieves high resolution of [Formula: see text] within unprecedentedly large DOF of 3.2 mm, more than 27 times the DOF of the probe without performing focus adjustment for MIF. The superior performance is first demonstrated by imaging both phantoms and animals including mice and zebrafish in vivo by linear scanning. Further, in vivo endoscopic imaging of a rat's rectum by rotary scanning of the probe is conducted to showcase the capability of adjustable focus. Our work opens new perspectives for PAE biomedical applications.

Land Use Changes Influence the Soil Enzymatic Activity and Nutrient Status in the Polluted Taojia River Basin in Sub-Tropical China.

Different land use practices may improve soil quality or lead to soil deterioration. Recently, environmental problems, such as heavy pollution and soil erosion, have led to serious land degradation in the Taojia River basin. In this study, we explored the soil fertility characteristics (mechanical composition; pH; soil organic matter (SOM); soil total nitrogen (TN); and the activity of four enzymes, i.e., urease, hydrogen peroxide, alkaline phosphatase, and sucrose enzymes) under different types of land use in the Taojia River basin. Soil samples were taken from 0-10 cm, 10-20 cm, and 20-40 cm depths from four different land use types that were widely used in the Taojia river basin, including cultivated land, vegetable fields, woodlands, and wastelands. The results showed that the soil enzyme activity and the constituents of the soil were closely related and significantly affected each other (p < 0.05). Woodland soil exhibited the highest content of SOM in all soil depths. Soil total nitrogen mainly depended on the accumulation of biomass and the decomposition intensity of organic matter, so the changes in TN followed the trends of the changes in SOM. Woodland soil showed an improved mechanical composition. We were also able to observe an increased clay content in woodland soil. Woodland soil also exhibited the reversal of soil desertification and an increase in nutrient/water retention capacity. Therefore, an increase in woodland areas would be an appropriate goal in terms of land use in order to improve the eco-environmental quality of the Taojia River basin.

[Response of Soil Respiration Rates to Soil Temperature and Moisture at Different Soil Depths of Caragana korshinskii Plantation in the Loess-Hilly Region].

It is of great significance to clarify the influence of soil temperature and moisture on soil respiration rate and its characteristics in ecologically fragile regions under the background of climate change for the accurate assessment and prediction of carbon budgets in this region. The average CO2 concentration and soil temperature and moisture at different soil depths (10, 50, and 100 cm) were measured using a CO2 analyzer and temperature and moisture sensors. The soil respiration rate was calculated using Fick's first diffusion coefficient method. The dynamic characteristics of soil temperature, soil moisture, and soil respiration rate in different soil depths were explored, and the response of soil respiration rate to soil temperature and moisture were further analyzed. The results showed that the diurnal variation in soil respiration rate decreased significantly with the increase in soil depth (P<0.05), and the peak time lagged behind. Soil respiration rate in adjacent soil depths (10, 50, and 100 cm) lagged 1 h from top to bottom. The monthly variation in soil respiration rate was a multi-peak curve, in which the maximum soil respiration rates of 10, 50, and 100 cm soil depths were on July 25th, August 6th, and August 10th, reaching 13.96, 2.96, and 1.47 µmol·(m2·s)-1, respectively. The effect of soil temperature on soil respiration rate decreased with the increase in soil depth. Soil temperature at 50 cm and below had no significant effect on soil respiration rate (P>0.05). The fitting index of 10 cm soil depth was the best (R2=0.96), but the fitting indexes of 50 cm and 100 cm soil depths were poor (R2=0.00 and R2=0.01, respectively). The temperature sensitivity coefficient Q10 decreased with the increase in soil depth. Soil moisture in different soil depths had significant effects on soil respiration rate (P<0.05), and the quadratic fitting indicated that 50 cm (R2=0.35)>10 cm (R2=0.22)>100 cm (R2=0.31). The combined effects of soil temperature and moisture in different soil depths could explain 96%, 6%-50%, and 22%-24% of soil respiration rate, respectively. In summary, the effects of soil temperature and moisture at different soil depths of the Caragana korshinskii plantation in the loess-hilly region on soil respiration rate differed. The soil respiration rate of the 10 cm soil depth was affected by the comprehensive effect of soil temperature and moisture; however, the relative contribution of soil temperature was higher, and soil moisture at and below a soil depth of 50 cm was the key factor. These results could help improve predictions on the impact of future climate change on the carbon cycle of terrestrial ecosystems in the region and provide a theoretical basis for greenhouse gas regulation in the future.

Distributed and Time-Delayed k-Winner-Take-All Network for Competitive Coordination of Multiple Robots.

In this article, a distributed and time-delayed k-winner-take-all (DT-kWTA) network is established and analyzed for competitively coordinated task assignment of a multirobot system. It is considered and designed from the following three aspects. First, a network is built based on a k-winner-take-all (kWTA) competitive algorithm that selects k maximum values from the inputs. Second, a distributed control strategy is used to improve the network in terms of communication load and computational burden. Third, the time-delayed problem prevalent in arbitrary causal systems (especially, in networks) is taken into account in the proposed network. This work combines distributed kWTA competition network with time delay for the first time, thus enabling it to better handle realistic applications than previous work. In addition, it theoretically derives the maximum delay allowed by the network and proves the convergence and robustness of the network. The results are applied to a multirobot system to conduct its robots' competitive coordination to complete the given task.

High-fidelity deconvolution for acoustic-resolution photoacoustic microscopy enabled by convolutional neural networks.

Acoustic-resolution photoacoustic microscopy (AR-PAM) image resolution is determined by the point spread function (PSF) of the imaging system. Previous algorithms, including Richardson-Lucy (R-L) deconvolution and model-based (MB) deconvolution, improve spatial resolution by taking advantage of the PSF as prior knowledge. However, these methods encounter the problems of inaccurate deconvolution, meaning the deconvolved feature size and the original one are not consistent (e.g., the former can be smaller than the latter). We present a novel deep convolution neural network (CNN)-based algorithm featuring high-fidelity recovery of multiscale feature size to improve lateral resolution of AR-PAM. The CNN is trained with simulated image pairs of line patterns, which is to mimic blood vessels. To investigate the suitable CNN model structure and elaborate on the effectiveness of CNN methods compared with non-learning methods, we select five different CNN models, while R-L and directional MB methods are also applied for comparison. Besides simulated data, experimental data including tungsten wires, leaf veins, and in vivo blood vessels are also evaluated. A custom-defined metric of relative size error (RSE) is used to quantify the multiscale feature recovery ability of different methods. Compared to other methods, enhanced deep super resolution (EDSR) network and residual in residual dense block network (RRDBNet) model show better recovery in terms of RSE for tungsten wires with diameters ranging from 30 µ m to 120 µ m . Moreover, AR-PAM images of leaf veins are tested to demonstrate the effectiveness of the optimized CNN methods (by EDSR and RRDBNet) for complex patterns. Finally, in vivo images of mouse ear blood vessels and rat ear blood vessels are acquired and then deconvolved, and the results show that the proposed CNN method (notably RRDBNet) enables accurate deconvolution of multiscale feature size and thus good fidelity.

Ecological adaptation shaped the genetic structure of homoploid ferns against strong dispersal capacity.

The formation of spatial genetic structure with the presence of extensive gene flow, an evolutionary force which is generally expected to eliminate population-specific variation and maintain genetic homogeneity, remains poorly understood. Homosporous ferns, which spread by spores through wind and possess long distance dispersal capacity, provide an ideal system to investigate such a process. Here, using a homoploid fern lineage, the Athyrium sinense complex, we used reduced-representation genomic data to examine spatial genetic structure and explored potential driving forces including geographical distance, environment, climatic history and external dispersal constraints. Our findings showed a clear north-south divergence at the genetic, morphological and ecological levels between both sides of 35°N in East Asia. Fluctuant and heterogeneous climatic condition was demonstrated to play a crucial role during the formation of the divergence. Our results suggested that this lineage was able to migrate southward and colonize new habitat as a result of the Quaternary climatic fluctuation. Furthermore, the present genetic structure is attributed to adaptation to heterogeneous environments, especially temperature difference. In addition to ecological adaptation, we found clues showing that canopy density, wind direction as well as habitat continuity were all likely to constrain the effect of gene flow. These results demonstrated a diversification process without ploidy changes in ferns providing new insights for our present knowledge on ferns' spatio-temporal evolutionary pattern. In particular, our study highlights the influence of environmental heterogeneity in driving genetic divergence against strong dispersal capacity.

Image enhancement in acoustic-resolution photoacoustic microscopy enabled by a novel directional algorithm.

By considering the line pattern of acoustic-resolution photoacoustic microscopy (AR-PAM) vessel images, we develop modified algorithms for synthetic aperture focusing technique (SAFT) and deconvolution based on a directional approach to enhance images. The modified algorithms consist of Fourier accumulation SAFT (FA-SAFT) and directional model-based (D-MB) deconvolution. To evaluate the performance of our algorithms, we conduct a series of imaging experiments and apply our algorithms, and existing SAFT and deconvolution algorithms are also applied for side-by-side comparison. By imaging tungsten wire phantom, our algorithms enable full width at half maximum of 26 - 31 µm over depth of focus of 1.8 mm and minimum resolvable distance of 46 - 49 µm, besting existing SAFT and deconvolution algorithms. Imaging of leaf skeleton phantom and in vivo imaging of mouse blood vessels also prove that our algorithm is capable of providing high-resolution, high-signal-to-noise ratio, and good-fidelity results for complex structures and for in vivo applications, especially for the images with the line pattern. The proposed directional approach can not only be used in AR-PAM but also in other imaging modalities to deal with the line pattern, such as FA-SAFT for ultrasound imaging and D-MB deconvolution for optical coherence tomography angiography.

Macroscopic and Microscopic Properties of Cement Paste with Carbon Dioxide Curing.

Carbon dioxide is the main component of greenhouse gases, which are responsible for an increase in global temperature. The utilization of carbon dioxide in cement-based materials is an effective way to capture this gas. In this paper, the influence of carbon dioxide curing on the setting time, the electrical resistivity, dry shrinkage ratio, water absorption by unit area and mechanical strengths (flexural and compressive strengths) were determined. The scanning electron microscope, X-ray diffraction and thermogravimetric analysis were obtained to investigate the mechanism of carbonation reaction of cement paste. Water-cement ratios of cement paste were selected to be 0.3, 0.4 and 0.5. Results showed that carbon dioxide curing could accelerate the setting of cement paste. The electrical resistivity decreased with the increasing water-cement ratio and increased with the carbon dioxide curing. Moreover, the evaluation function for the curing age and dry shrinkage rate or the mechanical strengths fit well with the positive correlation quadratic function. The water absorption by unit area increased linearly with the testing time. The carbon dioxide curing led to increasing the mechanical strengths and the dry shrinkage ratio. Meanwhile, the carbon dioxide curing demonstrated a decreasing effect on the water absorption by unit area. The mechanical strengths were improved by the carbon dioxide curing and increased in the form of quadratic function with the curing age. As obtained from the microscopic findings, that the carbon dioxide curing could accelerate the reaction of cement and improve the compactness of cement paste.

Deep learning methods for 3D structural proteome and interactome modeling.

Bolstered by recent methodological and hardware advances, deep learning has increasingly been applied to biological problems and structural proteomics. Such approaches have achieved remarkable improvements over traditional machine learning methods in tasks ranging from protein contact map prediction to protein folding, prediction of protein-protein interaction interfaces, and characterization of protein-drug binding pockets. In particular, emergence of ab initio protein structure prediction methods including AlphaFold2 has revolutionized protein structural modeling. From a protein function perspective, numerous deep learning methods have facilitated deconvolution of the exact amino acid residues and protein surface regions responsible for binding other proteins or small molecule drugs. In this review, we provide a comprehensive overview of recent deep learning methods applied in structural proteomics.

Research Progress of Heavy Ion Radiotherapy for Non-Small-Cell Lung Cancer.

Non-small-cell lung cancer (NSCLC) has a high incidence and poses a serious threat to human health. However, the treatment outcomes of concurrent chemoradiotherapy for non-small-cell lung cancer are still unsatisfactory, especially for high grade lesions. As a new cancer treatment, heavy ion radiotherapy has shown promising efficacy and safety in the treatment of non-small-cell lung cancer. This article discusses the clinical progress of heavy ion radiotherapy in the treatment of non-small-cell lung cancer mainly from the different cancer stages, the different doses of heavy ion beams, and the patient's individual factors, and explores the deficiency of heavy ion radiotherapy in the treatment of non-small-cell lung cancer and the directions of future research, in order to provide reference for the wider and better application of heavy ion radiotherapy in the future.

Cerebrovascular imaging in vivo by non-contact photoacoustic microscopy based on photoacoustic remote sensing with a laser diode for interrogation.

Photoacoustic microscopy (PAM) is a unique tool for biomedical applications because it can visualize optical absorption contrast in vivo. Recently, non-contact PAM based on non-interferometric photoacoustic remote sensing (PARS), termed PARS microscopy, has shown promise for selected imaging applications. A variety of superluminescent diodes (SLDs) have been employed in the PARS microscopy system as the interrogation light source. Here, we investigate the use of a low-cost laser diode (LD) as the interrogation light source in PARS microscopy, termed PARS-LD. A side-by-side comparison of PARS-LD and a PARS microscopy system using an SLD was conducted that showed comparable performance in terms of resolution and signal-to-noise ratio. More importantly, for the first time to our knowledge, in vivo PAM imaging of mouse brain vessels was conducted in a non-contact manner, and the results show that PARS-LD provides great performance.

Adsorption of Diclofenac Sodium by Aged Degradable and Non-Degradable Microplastics: Environmental Effects, Adsorption Mechanisms.

Microplastics (MPs) are novel pollutants, which can carry toxic contaminants and are released in biota and accumulate. The adsorption behavior of MPs and aged MPs has attracted extensive attention. In this paper, the aging process of polystyrene (PS) and poly (butyleneadipate-co-terephthalate) (PBAT) plastics under ultraviolet (UV) irradiation at a high temperature and their adsorption properties for the contaminant diclofenac sodium (DCF) before and after aging was investigated. There are many factors affecting the adsorption capacity of MPs. In this experiment, three aspects of MPs, organic pollutants, and environmental factors are explored. The Freundlich model as well as the pseudosecondary kinetic model is more applicable to the process of DCF adsorption by MPs. The main effects of adsorption of organic pollutants by MPs are electrostatic interactions, hydrogen-halogen bonds, and hydrophobic interactions. The adsorption capacity of the UV-aged MPs on DCF is significantly enhanced, and the order of adsorption capacity is Q(A-PBAT) (27.65 mg/g) > Q (A-PS) (23.91 mg/g) > Q (PBAT) (9.30 mg/g) > Q (PS) (9.21 mg/g). The results show that more active sites are generated on the surface of MPs after aging, which can enhance their adsorption capacity for organic pollutants. This adsorption mechanism will increase their role as contaminant carriers in the aquatic food chain.

Plastid phylogenomics provides novel insights into the infrafamilial relationship of Polypodiaceae.

The polygrammoids (Polypodiaceae) are the most species-rich and diversified epiphytic fern lineages, and hold an important role to understand the deep diverging events and rapid adaptation to changing environments in the plant tree of life. Despite progress in the phylogeny of this group of ferns in previous multilocus phylogenetic studies, uncertainty remains especially in backbone relationships among closely related clades, and the phylogenetic placement of recalcitrant species or lineages. Here, we investigated the deep phylogenetic relationships within Polypodiaceae by sampling all major lineages and using 81 plastid genomes (plastomes), of which 70 plastomes were newly sequenced with high-throughput sequencing technology. Based on parsimony, maximum-likelihood, Bayesian and multispecies coalescent analyses of genome skimming data, we achieved a better resolution of the backbone phylogeny of Polypodiaceae. Using simulated data matrices, we detected that potential phylogenetic artefacts, such as long-branch attraction and insufficient taxonomic sampling, may have a confounding impact on the incongruence of phylogenetic inferences. Furthermore, our phylogenetic analyses offer greater resolution than previous multilocus studies, providing a robust framework for future phylogenetic implications on the subfamilial taxonomy of Polypodiaceae. Our phylogenomic study not only demonstrates the advantage of a character-rich plastome dataset for resolving the recalcitrant lineages that have undergone rapid radiation, but also sheds new light on integrative explorations understanding the evolutionary history of large fern groups in the genomic era.

A 3D structural SARS-CoV-2-human interactome to explore genetic and drug perturbations.

Emergence of new viral agents is driven by evolution of interactions between viral proteins and host targets. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV-1 arose in part through rapid evolution along the interface between the spike protein and its human receptor ACE2, leading to increased binding affinity. To facilitate broader exploration of how pathogen-host interactions might impact transmission and virulence in the ongoing COVID-19 pandemic, we performed state-of-the-art interface prediction followed by molecular docking to construct a three-dimensional structural interactome between SARS-CoV-2 and human. We additionally carried out downstream meta-analyses to investigate enrichment of sequence divergence between SARS-CoV-1 and SARS-CoV-2 or human population variants along viral-human protein-interaction interfaces, predict changes in binding affinity by these mutations/variants and further prioritize drug repurposing candidates predicted to competitively bind human targets. We believe this resource ( http://3D-SARS2.yulab.org ) will aid in development and testing of informed hypotheses for SARS-CoV-2 etiology and treatments.