The determinant factors for map resolutions obtained using CryoEM single particle imaging method

The CryoEM single particle structure determination method has recently received broad attention in the field of structural biology. The structures can be resolved to near-atomic resolutions after model reconstructions from a large number of CryoEM images measuring molecules in different orientations. However, the determining factors for reconstructed map resolution need to be further explored. Here, we provide a theoretical framework in conjunction with numerical simulations to gauge the influence of several key factors to CryoEM map resolutions. If the projection image quality allows orientation assignment, then the number of measured projection images and the quality of each measurement(quantified using average signal-to-noise ratio) can be combined to a single factor, which is dominant to the resolution of reconstructed maps. Furthermore, the intrinsic thermal motion of molecules has significant effects on the resolution. These effects can be quantitatively summarized with an analytical formula that provides a theoretical guideline on structure resolutions for given experimental measurements.

In situ injectable hydrogel encapsulating Mn/NO-based immune nano-activator for prevention of postoperative tumor recurrence

Postoperative tumor recurrence remains a predominant cause of treatment failure. In this study, we developed an in situ injectable hydrogel, termed MPB-NO@DOX + ATRA gel, which was locally formed within the tumor resection cavity. The MPB-NO@DOX + ATRA gel was fabricated by mixing a thrombin solution, a fibrinogen solution containing all-trans retinoic acid (ATRA), and a Mn/NO-based immune nano-activator termed MPB-NO@DOX. ATRA promoted the differentiation of cancer stem cells, inhibited cancer cell migration, and affected the polarization of tumor-associated macrophages. The outer MnO2 shell disintegrated due to its reaction with glutathione and hydrogen peroxide in the cytoplasm to release Mn2+ and produce O2, resulting in the release of doxorubicin (DOX). The released DOX entered the nucleus and destroyed DNA, and the fragmented DNA cooperated with Mn2+ to activate the cGAS-STING pathway and stimulate an anti-tumor immune response. In addition, when MPB-NO@DOX was exposed to 808 nm laser irradiation, the Fe-NO bond was broken to release NO, which downregulated the expression of PD-L1 on the surface of tumor cells and reversed the immunosuppressive tumor microenvironment. In conclusion, the MPB-NO@DOX + ATRA gel exhibited excellent anti-tumor efficacy. The results of this study demonstrated the great potential of in situ injectable hydrogels in preventing postoperative tumor recurrence.

Computational design of proteins with novel structure and functions

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed.

Condensation of STM is critical for shoot meristem maintenance and salt tolerance in Arabidopsis

The shoot meristem generates the entire shoot system and is precisely maintained throughout the life cycle under various environmental challenges.In this study,we identified a prion-like domain(PrD)in the key shoot meristem regulator SHOOT MERISTEMLESS(STM),which distinguishes STM from other related KNOX1 proteins.We demonstrated that PrD stimulates STM to form nuclear condensates,which are required for maintaining the shoot meristem.STM nuclear condensate formation is stabilized by selected PrD-containing STM-interacting BELL proteins in vitro and in vivo.Moreover,condensation of STM promotes its interaction with the Mediator complex subunit MED8 and thereby enhances its transcriptional activity.Thus,condensate formation emerges as a novel regulatory mechanism of shoot meristem functions.Furthermore,we found that the formation of STM condensates is enhanced upon salt stress,which allows enhanced salt tolerance and increased shoot branching.Our findings highlight that the transcription factor partitioning plays an important role in cell fate determination and might also act as a tunable environmental acclimation mechanism.

Discretization and index-robust error analysis for constrained high-index saddle dynamics on the high-dimensional sphere

We develop and analyze numerical discretization to the constrained high-index saddle dynamics,the dynamics searching for the high-index saddle points confined on the high-dimensional unit sphere.Compared with the saddle dynamics without constraints,the constrained high-index saddle dynamics has more complex dynamical forms,and additional operations such as the retraction and vector transport are required due to the constraints,which significantly complicate the numerical scheme and the corresponding numerical analysis.Furthermore,as the existing numerical analysis results usually depend on the index of the saddle points implicitly,the proved numerical accuracy may be reduced if the index is high in many applications,which indicates the lack of robustness with respect to the index.To address these issues,we derive the error estimates for numerical discretization of the constrained high-index saddle dynamics on the high-dimensional sphere and then improve it by providing index-robust error analysis in an averaged norm by adjusting the relaxation parameters.The developed results provide mathematical support for the accuracy of numerical computations.

Extended Nernst–Planck Equation Incorporating Partial Dehydration Effect

Novel ionic transporting phenomena emerge as nanostructures approach the molecular scale.At the sub-2 nm scale,widely used continuum equations,such as the Nernst-Planck equation,break down.Here,we extend the Nernst-Planck equation by adding a partial dehydration effect.Our model agrees with the reported ion fluxes through graphene oxide laminates with sub-2 nm interlayer spacing,outperforming previous models.We also predict that the selectivity sequences of alkali metal ions depend on the geometries of the nanostructures.Our model opens a new avenue for the investigation of the underlying mechanisms in nanofluidics at the sub-2 nm scale.

A novel hyper-cube shrink algorithm to predict metabolic fluxes based on enzyme activity only

OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.

Differences in action potential propagation speed and axon initial segment plasticity between neurons from Sprague-Dawley rats and C57BL/6 mice

Action potentials(APs)in neurons are generated at the axon initial segment(AIS).AP dynamics,including initiation and propagation,are intimately associated with neuronal excitability and neurotransmitter release kinetics.Most learning and memory studies at the single-neuron level have relied on the use of animal models,most notably rodents.Here,we studied AP initiation and propagation in cultured hippocampal neurons from Sprague-Dawley(SD)rats and C57BL/6(C57)mice with genetically encoded voltage indicator(GEVI)-based voltage imaging.Our data showed that APs traveled bidirectionally in neurons from both species;forward-propagating APs(fpAPs)had a different speed than backpropagating APs(bpAPs).Additionally,we observed distinct AP propagation characteristics in AISs emerging from the somatic envelope compared to those originating from dendrites.Compared with rat neurons,mouse neurons exhibited higher bpAP speed and lower fpAP speed,more distally located ankyrin G(AnkG)in AISs,and longer Nav1.2 lengths in AISs.Moreover,during AIS plasticity,AnkG and Nav1.2 showed distal shifts in location and shorter lengths of labeled AISs in rat neurons;in mouse neurons,however,they showed a longer AnkG-labeled length and more distal Nav1.2 location.Our findings suggest that hippocampal neurons in SD rats and C57 mice may have different AP propagation speeds,different AnkG and Nav1.2 patterns in the AIS,and different AIS plasticity properties,indicating that comparisons between these species must be carefully considered.

Cryo-EM Data Statistics and Theoretical Analysis of KaiC Hexamer

Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.

Specific pupylation as IDEntity reporter(SPIDER)for the identification of protein-biomolecule interactions

Protein-biomolecule interactions play pivotal roles in almost all biological processes.For a biomolecule of interest,the identification of the interacting protein(s)is essential.For this need,although many assays are available,highly robust and reliable methods are always desired.By combining a substrate-based proximity labeling activity from the pupylation pathway of Mycobacterium tuberculosis and the streptavidin(SA)-biotin system,we developed the Specific Pupylation as IDEntity Reporter(SPIDER)method for identifying protein-biomolecule interactions.Using SPIDER,we validated the interactions between the known binding proteins of protein,DNA,RNA,and small molecule.We successfully applied SPIDER to construct the global protein interactome for m^(6)A and m RNA,identified a variety of uncharacterized m^(6)A binding proteins,and validated SRSF7 as a potential m^(6)A reader.We globally identified the binding proteins for lenalidomide and Cob B.Moreover,we identified SARS-CoV-2-specific receptors on the cell membrane.Overall,SPIDER is powerful and highly accessible for the study of proteinbiomolecule interactions.

Recent developments in computational modelling of nucleation in phase transformations

Nucleation is one of the most common physical phenomena in physical,chemical,biological and materials sciences.Owing to the complex multiscale nature of various nucleation events and the difficulties in their direct experimental observation,development of effective computational methods and modeling approaches has become very important and is bringing new light to the study of this challenging subject.Our discussions in this manuscript provide a sampler of some newly developed numerical algorithms that are widely applicable to many nucleation and phase transformation problems.We first describe some recent progress on the design of efficient numerical methods for computing saddle points and minimum energy paths,and then illustrate their applications to the study of nucleation events associated with several different physical systems.

Structure for energy cycle: a unique status of the second law of thermodynamics for living systems

Distinguishing things from beings, or matters from lives, is a fundamental question. Extending E. Schr?dinger's neg-entropy and I. Prigogine's dissipative structure, we propose a chemical kinetic view that the earliest "live" process is embedded essentially in a special interaction between a pair of specific components under a particular, corresponding environmental conditions. The interaction exists as an inter-molecular-force-bond complex(IMFBC) that couples two separate chemical processes: one is the spontaneous formation of the IMFBC driven by a decrease of Gibbs free energy as a dissipative process; while the other is the disassembly of the IMFBC driven thermodynamically by free energy input from the environment. The two chemical processes coupled by the IMFBC originated independently and were considered non-living on Earth, but the IMFBC coupling of the two can be considered as the earliest form of metabolism: the first landmark on the path from things to a being. The dynamic formation and disassembly of the IMFBC, as a composite individual, follows a principle designated as "… structure for energy for structure for energy…", the cycle continues; and for short it will be referred to as "structure for energy cycle". With additional features derived from this starting point, the IMFBC-centered "live" process spontaneously evolved into more complex living organisms with the characteristics currently known.

Towards a New Paradigm for Brain-inspired Computer Vision

Brain-inspired computer vision aims to learn from biological systems to develop advanced image processing techniques.However,its progress so far is not impressing.We recognize that a main obstacle comes from that the current paradigm for brain-inspired computer vision has not captured the fundamental nature of biological vision,i.e.,the biological vision is targeted for processing spatio-temporal patterns.Recently,a new paradigm for developing brain-inspired computer vision is emerging,which emphasizes on the spatio-temporal nature of visual signals and the brain-inspired models for processing this type of data.In this paper,we review some recent primary works towards this new paradigm,including the development of spike cameras which acquire spiking signals directly from visual scenes,and the development of computational models learned from neural systems that are specialized to process spatio-temporal patterns,including models for object detection,tracking,and recognition.We also discuss about the future directions to improve the paradigm.

Systematically investigating the key features of the DNase deactivated Cpf1 for tunable transcription regulation in prokaryotic cells

With a unique crRNA processing capability,the CRISPR associated Cpf1 protein holds great potential for multiplex gene regulation.Unlike the well-studied Cas9 protein,however,conversion of Cpf1 to a transcription regulator and its related properties have not been systematically explored yet.In this study,we investigated the mutation schemes and crRNA requirements for the DNase deactivated Cpf1(dCpf1).By shortening the direct repeat sequence,we obtained genetically stable crRNA co-transcripts and improved gene repression with multiplex targeting.A screen of diversity-enriched PAM library was designed to investigate the PAMdependency of gene regulation by dCpf1 from Francisella novicida and Lachnospiraceae bacterium.We found novel PAM patterns that elicited strong or medium gene repressions.Using a computational algorithm,we predicted regulatory outputs for all possible PAM sequences,which spanned a large dynamic range that could be leveraged for regulatory purposes.These newly identified features will facilitate the efficient design of CRISPR-dCpf1 based systems for tunable multiplex gene regulation.

Mean field study of a propagation-turnover lattice model for the dynamics of histone marking

We present a mean field study of a propagation-turnover lattice model, which was proposed by Hodges and Crabtree [Proc.Nat. Acad. Sci. 109, 13296(2012)] for understanding how posttranslational histone marks modulate gene expression in mammalian cells. The kinetics of the lattice model consists of nucleation, propagation and turnover mechanisms, and exhibits second-order phase transition for the histone marking domain. We showed rigorously that the dynamics essentially depends on a non-dimensional parameter κ = k+/k-, the ratio between the propagation and turnover rates, which has been observed in the simulations. We then studied the lowest order mean field approximation, and observed the phase transition with an analytically obtained critical parameter. The boundary layer analysis was utilized to investigate the structure of the decay profile of the mark density. We also studied the higher order mean field approximation to achieve sharper estimate of the critical transition parameter and more detailed features. The comparison between the simulation and theoretical results shows the validity of our theory.

scEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type Perception

Current cell-type annotation tools for single-cell RNA sequencing(sc RNA-seq)data mainly utilize well-annotated source data to help identify cell types in target data.However,on account of privacy preservation,their requirements for raw source data may not always be satisfied.In this case,achieving feature alignment between source and target data explicitly is impossible.Additionally,these methods are barely able to discover the presence of novel cell types.A subjective threshold is often selected by users to detect novel cells.We propose a universal annotation framework for sc RNA-seq data called sc EMAIL,which automatically detects novel cell types without accessing source data during adaptation.For new cell-type identification,a novel cell-type perception module is designed with three steps.First,an expert ensemble system measures uncertainty of each cell from three complementary aspects.Second,based on this measurement,bimodality tests are applied to detect the presence of new cell types.Third,once assured of their presence,an adaptive threshold via manifold mixup partitions target cells into‘‘known”and‘‘unknown”groups.Model adaptation is then conducted to alleviate the batch effect.We gather multi-order neighborhood messages globally and impose local affinity regularizations on‘‘known”cells.These constraints mitigate wrong classifications of the source model via reliable self-supervised information of neighbors.sc EMAIL is accurate and robust under various scenarios in both simulation and real data.It is also flexible to be applied to challenging single-cell ATAC-seq data without loss of superiority.The source code of sc EMAIL can be accessed at https://github.com/aster-ww/sc EMAIL and https://ngdc.cncb.ac.cn/biocode/tools/BT007335/releases/v1.0.

How should bioinformatics Pls run wet-labs?

With the rapid development of biotechnology,data-driven bioinformatics research is increasingly dependent on data generation from biological wet-labs.At the same time,to gain in-depth knowledge of various biological systems,conventional biology laboratories have become more reliant on the establishment and optimization of advanced bioinformatics methods.Many bioinformatics labs are debating whether to build their own wet-bench or to seek collaborations,while many wet-bench labs are also confused over whether they should build their own dry-labs or likewise seek collaborations.