Protein circuit design using de novo proteins

Protein-based biological circuits enable customized control of cellular functions, and de novo protein design enables circuit functionalities that are not possible by repurposing natural proteins. Here, I highlight recent progress in protein circuit design, including CHOMP, developed by Gao et al., and SPOC, developed by Fink et al.     

ParaSiteDB – A user-friendly database for managing a parasitological collection

ParaSiteDB is an application for arranging and managing a parasitological collection. It has been designed to provide a user-friendly, easily manageable and searchable site and is suitable for small to bigger collections.The source code of the application is available on GitHub: https://github.com/goobar4/aacrg.The demonstration version of the application is available on https://syrota.info/wormbasehttp://syrota.info/wormbase.     

ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds

Synthetic biology and metabolic engineering rely on computational search tools for predictions of novel biosynthetic pathways to industrially important compounds, many of which are derived from aromatic amino acids. Pathway search tools vary in their scope of covered reactions and compounds, as well as in metrics for ranking and evaluation. In this work, we present a new computational resource called ARBRE: Aromatic compounds RetroBiosynthesis Repository and Explorer. It consists of a comprehensive biochemical reaction network centered around aromatic amino acid biosynthesis and a computational toolbox for navigating this network. ARBRE encompasses over 33′000 known and 390′000 novel reactions predicted with generalized enzymatic reactions rules and over 74′000 compounds, of which 19′000 are known to biochemical databases and 55′000 only to PubChem. Over 1′000 molecules that were solely part of the PubChem database before and were previously impossible to integrate into a biochemical network are included into the ARBRE reaction network by assigning enzymatic reactions. ARBRE can be applied for pathway search, enzyme annotation, pathway ranking, visualization, and network expansion around known biochemical pathways and products of lignin degradation to predict valuable compound derivations. In line with the standards of open science, we have made the toolbox freely available to the scientific community on git (https://github.com/EPFL-LCSB/ARBRE) and we provide the web-version at http://lcsb-databases.epfl.ch/arbre/. We envision that ARBRE will provide the community with a new computational resource and comprehensive search tool to predict and rank pathways towards industrially important aromatic compounds.     

The multi-kinase inhibitor lenvatinib interacts with the HDAC inhibitor entinostat to kill liver cancer cells

Prior studies from our group have combined the multi-kinase inhibitor sorafenib with HDAC inhibitors in GI tumor cells that resulted in the trials NCT02349867 and NCT01075113. The multi-kinase inhibitor lenvatinib, for the treatment of liver cancer, has fewer negative sequelae than sorafenib. We determined the mechanisms by which lenvatinib interacted with the HDAC inhibitor entinostat to kill hepatoma cells. Lenvatinib and entinostat interacted in an additive to greater-than-additive fashion to kill liver cancer cells. The drugs inactivated mTORC1 and mTORC2 and interacted to further increase the phosphorylation of ATM, ATG13 and eIF2α. Elevated eIF2α phosphorylation was responsible for reduced MCL-1 and BCL-XL expression and for increased Beclin1 and ATG5 expression. Over-expression of BCL-XL or knock down of Beclin1 or ATG5, significantly reduced killing. The drugs synergized to elevate ROS production; activation of ATM was ROS-dependent. ATM activation was required for enhanced phosphorylation of γH2AX, eIF2α and ATG13 S318. The drug combination reduced histone deacetylase protein expression which required autophagy. Knock down of HDACs1/2/3 prevented the lenvatinib and entinostat combination from regulating PD-L1 and MHCA expression. Collectively, our data demonstrate that lenvatinib and entinostat interact to kill liver cancer cells via ROS-dependent activation of ATM and inactivation of eIF2α, resulting in greater levels of toxic autophagosome formation and reduced expression of protective mitochondrial proteins.     

Molecular information technology with DNA

Qian and Winfree constructed complex biochemical circuits with computation capability from scratch, demonstrating the programmability of biomolecules. One day, programming molecular information processing may be just like how electronic machines are programmed today, with exciting applications in nanoscale science and biotechnology.     

Saving eyesight,one gene at a time

Kai Yao’s group used prime editing to repair a blindness-causing mutation in the Pde6b gene in the mouse retina. This breakthrough was made possible by a Cas9 nickase that is not constrained by a protospacer adjacent motif (PAM) sequence requirement. This innovation brings prime editing technology one step closer to correcting disease-causing mutations at will.     

A comprehensive review on the phytochemistry,pharmacokinetics, and antidiabetic effect of Ginseng

BackgroundRadix Ginseng, one of the well-known medicinal herbs, has been used in the management of diabetes and its complications for more than 1000 years.PurposeThe aim of this review is devoted to summarize the phytochemistry and pharmacokinetics of Ginseng, and provide evidence for the antidiabetic effects of Ginseng and its ingredients as well as the underlying mechanisms involved.MethodsFor the purpose of this review, the following databases were consulted: the PubMed Database (https://pubmed.ncbi.nlm.nih.gov), Chinese National Knowledge Infrastructure (http://www.cnki.net), National Science and Technology Library (http://www.nstl.gov.cn/), Wanfang Data (http://www.wanfangdata.com.cn/) and the Web of Science Database (http://apps.webofknowledge.com/).ResultsGinseng exhibits glucose-lowering effects in different diabetic animal models. In addition, Ginseng may prevent the development of diabetic complications, including liver, pancreas, adipose tissue, skeletal muscle, nephropathy, cardiomyopathy, retinopathy, atherosclerosis and others. The main ingredients of Ginseng include ginsenosides and polysaccharides. The underlying mechanisms whereby this herb exerts antidiabetic activities may be attributed to the regulation of multiple signaling pathways, including IRS1/PI3K/AKT, LKB1/AMPK/FoxO1, AGEs/RAGE, MAPK/ERK, NF-κB, PPARδ/STAT3, cAMP/PKA/CERB and HIF-1α/VEGF, etc. The pharmacokinetic profiles of ginsenosides provide valuable information on therapeutic efficacy of Ginseng in diabetes. Although Ginseng is well-tolerated, dietary consumption of this herb should follow the doctors’ advice.ConclusionGinseng may offer an alternative strategy in protection against diabetes and its complications through the regulations of the multi-targets via various signaling pathways. Efforts to understand the underlying mechanisms with strictly-controlled animal models, combined with well-designed clinical trials and pharmacokinetic evaluation, will be important subjects of the further investigations and weigh in translational value of this herb in diabetes management.     

Organizations in reaction-diffusion systems: Effects of diffusion and boundary conditions

Chemical Organization Theory (COT) has been successfully applied to analyze complex reaction networks where species interact and new species can emerge. The COT has been well studied, but is yet to analyze high dimensional systems dynamics over time equivalent to ordinary differential equations. Moreover, spatial effects, such as diffusion and boundary conditions have also not been considered yet. Here, we extend the COT to cope with reaction-diffusion systems. Thereby we focus on the effects of diffusion and various boundary conditions. In order to demonstrate the effectiveness of our approach, we analyze two models based on partial differential equations, one of which is on HIV virus dynamics.The analysis shows interesting organizational structures when using different ranges of diffusion rates, as well as for Dirichlet and positive Neumann boundary conditions. The advantage of this novel approach is that it is based solely on the model structure (reaction rules) but is independent of kinetic details, such as rate constants. Hence, it copes with high-dimensional systems without the need of numerical simulations, and it can be applied without detailed mathematical knowledge. Our tool is available, without restriction at https://github.com/stephanpeter/orgs-rds.     

Viral sponges sequester nucleotide signals to inactivate immunity

Bacteria synthesize specialized nucleotide signals to control anti-phage defense. Two papers – by Huiting et al. and Jenson et al. – now reveal that bacteriophages encode protein ‘sponges’ that sequester cyclic oligonucleotide immune signals and inactivate host antiviral immunity.     

Dual function of the CHS3-CSA1 immune receptor pair

Plant nucleotide-binding leucine-rich repeat (NLR) receptors mediate specific recognition of pathogen effectors to initiate effector-triggered immunity. Recently, studies by Schulze et al., Yang et al., and Gu et al. collectively show that the Arabidopsis (Arabidopsis thaliana) NLR pair CHS3-CSA1 acts through two distinct activation modes to recognize different pathogen effectors, thus revealing the dual function of the CHS3-CSA1 pair in plant disease resistance.     

Feeding the world sustainably: efficient nitrogen use

Globally, overuse of nitrogen (N) fertilizers in croplands is causing severe environmental pollution. In this context, Gu et al. suggest environmentally friendly and cost-effective N management practices and Hamani et al. highlight the use of microbial inoculants to improve crop yields, while reducing N-associated environmental pollution and N-fertilizer use.     

Wildlife 3D multi-object tracking

The study of wildlife populations and species has gained increased relevance due to significant endangerment, loss of habitats and world climate change. Using camera traps for monitoring is a common method to estimate species diversity, occupancy and relative abundance. We present a 3D multi-object tracking method for wildlife camera trapping using RGB-D cameras. We infer precise three-dimensional pose estimations of individual animals (i.e. locations and orientations) and also three-dimensional estimations of their observed movements, including velocity estimations. More precisely, we achieved a scaled Average Multi-Object Tracking Accuracy (sAMOTA) of 88.43%. The code is available athttps://github.com/m-klasen/3D_wildlife_tracking.     

pH regulates peptide–receptor perception

Diverse plant small peptides are perceived by their corresponding receptors to mediate local or long-distance intercellular communications in various developmental and adaptive programs; notably, the mechanisms of peptide–receptor perception remain largely unrevealed. Two reports (Liu et al.; Diaz-Ardila et al.) shed light on how pH regulates peptide–receptor perception.     

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.     

Measuring tree-ring widths using the CooRecorder software application

We present a brief overview of how to measure tree-ring widths in the software application CooRecorder (Cybis Elektronik & Data AB) for tree-ring analysis complementing two video tutorials. The first tutorial covers the basics of opening files, measuring ring widths, preliminary crossdating with a reference chronology, and setting dates. The second tutorial covers setting earlywood-latewood boundaries, measuring across cracks, inserting locally absent or missing rings, manual adjustments, and metadata. The video tutorials can be found here https://www.youtube.com/watch?v=c-GNKHVUj9I and here https://www.youtube.com/watch?v=xO7Phc93xyM&t=3s. Videos have been closed-captioned in English. Video is also accessible via Mendeley Data, https://doi.org/10.17632/r3v7236kkz.1.     

The bioprocess TEA calculator: An online technoeconomic analysis tool to evaluate the commercial competitiveness of potential bioprocesses

Techno-economic analysis connects R&D, engineering, and business. By linking process parameters to financial metrics, it allows researchers to understand the factors controlling the potential success of their technologies. In particular, metabolic and bioprocess engineering, as disciplines, are aimed at engineering cells to synthesize products with an ultimate goal of commercial deployment. As a result it is critical to be able to understand the potential impact of strain engineering strategies and lab scale results on commercial potential. To date, while numerous techno-economic models have been developed for a wide variety of bioprocesses, they have either required process engineering expertise to adapt and/or use or do not directly connect financial outcomes to potential strain engineering results. Despite the clear value of techno-economic analysis, these challenges have made it inaccessible to many researchers. I have developed this online calculator (https://bioprocesstea.com OR http://bioprocess-tea-calculator.herokuapp.com/) to make the basic capabilities of early-stage techno-economic analysis of bioprocesses readily accessible. The tool, currently focused on aerobic fermentation processes, can be used to understand the impact of fermentation level metrics on the commercial potential of a bioprocess for the production of a wide variety of organic molecules. Using the calculator, I review the commercially relevant targets for an aerobic bioprocess for the production of diethyl malonate.     

LigBind: Identifying Binding Residues for Over 1000 Ligands with Relation-Aware Graph Neural Networks

Identifying the interactions between proteins and ligands is significant for drug discovery and design. Considering the diverse binding patterns of ligands, the ligand-specific methods are trained per ligand to predict binding residues. However, most of the existing ligand-specific methods ignore shared binding preferences among various ligands and generally only cover a limited number of ligands with a sufficient number of known binding proteins. In this study, we propose a relation-aware framework LigBind with graph-level pre-training to enhance the ligand-specific binding residue predictions for 1159 ligands, which can effectively cover the ligands with a few known binding proteins. LigBind first pre-trains a graph neural network-based feature extractor for ligand-residue pairs and relation-aware classifiers for similar ligands. Then, LigBind is fine-tuned with ligand-specific binding data, where a domain adaptive neural network is designed to automatically leverage the diversity and similarity of various ligand-binding patterns for accurate binding residue prediction. We construct ligand-specific benchmark datasets of 1159 ligands and 16 unseen ligands, which are used to evaluate the effectiveness of LigBind. The results demonstrate the LigBind’s efficacy on large-scale ligand-specific benchmark datasets, and it generalizes well to unseen ligands. LigBind also enables accurate identification of the ligand-binding residues in the main protease, papain-like protease and the RNA-dependent RNA polymerase of SARS-CoV-2. The web server and source codes of LigBind are available at http://www.csbio.sjtu.edu.cn/bioinf/LigBind/ and https://github.com/YYingXia/LigBind/ for academic use.     

SWEETLEAD: an In Silico Database of Approved Drugs,Regulated Chemicals,and Herbal Isolates for Computer-Aided Drug Discovery

In the face of drastically rising drug discovery costs, strategies promising to reduce development timelines and expenditures are being pursued. Computer-aided virtual screening and repurposing approved drugs are two such strategies that have shown recent success. Herein, we report the creation of a highly-curated in silico database of chemical structures representing approved drugs, chemical isolates from traditional medicinal herbs, and regulated chemicals, termed the SWEETLEAD database. The motivation for SWEETLEAD stems from the observance of conflicting information in publicly available chemical databases and the lack of a highly curated database of chemical structures for the globally approved drugs. A consensus building scheme surveying information from several publicly accessible databases was employed to identify the correct structure for each chemical. Resulting structures are filtered for the active pharmaceutical ingredient, standardized, and differing formulations of the same drug were combined in the final database. The publically available release of SWEETLEAD (https://simtk.org/home/sweetlead) provides an important tool to enable the successful completion of computer-aided repurposing and drug discovery campaigns.