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Chimeric antigen receptor (CAR) T cell therapy has demonstrated remarkable outcomes in individuals with hematological malignancies, but its success has been hindered by barriers intrinsic to the tumor microenvironment (TME), particularly for solid tumors, where it has yet to make its mark. In this article, we provide an updated review and future perspectives on features of the TME that represent barriers to CART cell therapy efficacy, including competition for metabolic fuels, physical barriers to infiltration, and immunosuppressive factors. We then discuss novel and promising strategies to overcome these obstacles that are in preclinical development or under clinical investigation.doi.org/10.1016/j.omto.2022.03.009 - 2022

Developmental biology has grown into a data intensive science with the development of high-throughput imaging and multi-omics approaches. Machine learning is a versatile set of techniques that can help make sense of these large datasets with minimal human intervention, through tasks such as image segmentation, super- resolution microscopy and cell clustering. In this Spotlight, I introduce the key concepts, advantages and limitations of machine learning, and discuss how these methods are being applied to problems in developmental biology. Specifically, I focus on how machine learning is improving microscopy and single-cell ‘omics’ techniques and data analysis. Finally, I provide an outlook for the futures of these fields and suggest ways to foster new interdisciplinary developments.oi:10.1242/dev.188474 - 2021

Gene correction is often referred to as the gold standard for precise gene editing and while CRISPR‐ Cas systems continue to expand the toolbox for clinically relevant genetic repair, mechanistic hurdles still hinder widespread implementation. One of the most prominent challenges to precise CRISPR‐ directed point mutation repair centers on the prevalence of on‐site mutagenesis, wherein insertions and deletions appear at the targeted site following correction. Here, we introduce a pathway model for Homology Directed Correction, specifically point mutation repair, which enables a foundational analysis of genetic tools and factors influencing precise gene editing. To do this, we modified an in vitro gene editing system which utilizes a cell‐free extract, CRISPR‐Cas RNP and donor DNA template to catalyze point mutation repair. We successfully direct correction of four unique point mutations which include two unique nucleotide mutations at two separate targeted sites and visualize the repair profiles resulting from these reactions. This extension of the cell‐free gene editing system to model point mutation repair may provide insight for understanding the factors influencing precise point mutation correction.doi.org/10.1038/s41598-022-11808-2 - 2022

The modification of DNA or RNA backbones is an emerging technology for therapeutic oligonucleotides, synthetic biology and biotechnology. Despite a plethora of reported arti- ficial backbones, their vast potential is not fully utilised. Limited synthetic accessibility remains a major bottleneck for the wider application of backbone-modified oligonucleo- tides. Thus, a variety of readily accessible artificial backbones and robust methods for their introduction into oligonucleotides are urgently needed to utilise their full potential in therapeutics, synthetic biology and biotechnology.doi.org/10.1042/ETLS20210169 - 2021

Fluorescent nucleobase surrogates capable of Watson–Crick hydrogen bonding are essential probes of nucleic acid structure and dynamics, but their limited brightness and short absorption and emission wavelengths have rendered them unsuitable for single-molecule detection. Aiming to improve on these properties, we designed a new tricyclic pyrimidine nucleoside analogue with a push–pull conjugated system and synthesized it in seven sequential steps. The resulting C-linked 8-(diethylamino)benzo[b][1,8] naphthyridin-2(1H)-one nucleoside, which we name ABN, exhibits 3442 1⁄4 20 000 M1 cm1 and Fem,540 1⁄4 0.39 in water, increasing to Fem 1⁄4 0.50–0.53 when base paired with adenine in duplex DNA oligonucleotides. Single-molecule fluorescence measurements of ABN using both one-photon and two- photon excitation demonstrate its excellent photostability and indicate that the nucleoside is present to > 95% in a bright state with count rates of at least 15 kHz per molecule. This new fluorescent nucleobase analogue, which, in duplex DNA, is the brightest and most red-shifted known, is the first to offer robust and accessible single-molecule fluorescence detection capabilities.DOI: 10.1039/d0sc03903a - 2021

The monitoring of DNA and RNA biomarkers freely circulating in the blood constitutes the basis of innovative cancer detection methods based on liquid biopsy. Such methods are expected to provide new opportunities for a better understanding of cancer disease at the molecular level, thus contributing to improved patient outcomes. Advanced biosensors can advance possibilities for cancer-related nucleic acid biomarkers detection. In this context, peptide nucleic acids (PNAs) play an important role in the fabrication of highly sensitive biosensors. This review provides an overview of recently described PNA-based biosensors for cancer biomarker detection. One of the most striking features of the described detection approaches is represented by the possibility to detect target nucleic acids at the ultra-low concentration with the capability to identify single-base mutations.doi: 10.3390/molecules22111951 - 2017

Since the first report of DNAzyme by in vitro selection in 1994, catalytic DNA has investigated extensively, and their application has expanded continually in virtue of rapid advances in molecular biology and biotechnology. Nowadays, DNA is in the second prime time by way of DNA-based hybrid catalysts and DNA metalloenzymes in which helical chirality of DNA serves to asymmetric catalysis. DNA-based hybrid catalysts are attractive system to respond the demand of the times to pursuit green and sustainable society beyond traditional catalytic systems that value reaction efficiency. Herein, we highlight the recent advances and perspective of DNA-based hybrid catalysts with various aspects of DNA as a versatile scaffold for asymmetric synthesis. We hope that scientists in a variety of fields will be encouraged to join and promote remarkable evolution of this interesting research.doi.org/10.1002/tcr.202100333 - 2022

CRISPR systems have emerged as transformative tools for altering genomes in living cells with un- precedented ease, inspiring keen interest in increasing their specificity for perfectly matched targets. We have developed a novel approach for improving specificity by incorporating chemical modifications in guide RNAs (gRNAs) at specific sites in their DNA recognition sequence (‘guide sequence’) and systematically evaluating their on-target and off-target activities in biochemical DNA cleavage assays and cell-based assays. Our results show that a chemical modification (2′-O-methyl-3′-phosphonoacetate, or ‘MP’) incorporated at select sites in the ribose- phosphate backbone of gRNAs can dramatically re- duce off-target cleavage activities while maintaining high on-target performance, as demonstrated in clinically relevant genes. These findings reveal a unique method for enhancing specificity by chemically modifying the guide sequence in gRNAs. Our approach introduces a versatile tool for augmenting the performance of CRISPR systems for research, industrial and therapeutic applications.doi: 10.1093/nar/gkx1199 - 2018

Nucleotide monomers that hold two nucleobases each, i.e. double- headed nucleotides, have been shown to form two sets of functional Watson–Crick base pairs when incorporated into dsDNA, and they hereby behave as dinucleotides. To form the basis for fully modified double-headed nucleic acids (DhNA), we have prepared three new DhNA monomers and can now demonstrate that the molecular information of 10 Watson–Crick base pairs can be condensed to highly stable 5-mer DhNA duplexes.DOI: 10.1039/d1cc03539h - 2021

The RNA world concept1 is one of the most fundamental pillars of the origin of life theory. It predicts that life evolved from increasingly complex self-replicating RNA molecules. The question of how this RNA world then advanced to the next stage, in which proteins became the catalysts of life and RNA reduced its function predominantly to information storage, is one of the most mysterious chicken-and-egg conundrums in evolution. Here we show that non-canonical RNA bases, which are found today in transfer and ribosomal RNAs, and which are considered to be relics of the RNA world, are able to establish peptide synthesis directly on RNA. The discovered chemistry creates complex peptide-decorated RNA chimeric molecules, which suggests the early existence of an RNA–peptide world13 from which ribosomal peptide synthesis14 may have emerged. The ability to grow peptides on RNA with the help of non-canonical vestige nucleosides offers the possibility of an early co-evolution of covalently connected RNAs and peptides, which then could have dissociated at a higher level of sophistication to create the dualistic nucleic acid–protein world that is the hallmark of all life on Earth.doi.org/10.1038/s41586-022-04676-3 - 2022

In the evolutionary arms race against phage, bacteria have assembled a diverse arsenal of antiviral immune strategies. While the recently discovered DISARM (Defense Island System Associated with Restriction-Modification) systems can provide protection against a wide range of phage, the molecular mechanisms that underpin broad antiviral targeting but avoiding autoimmunity remain enigmatic. Here, we report cryo-EM structures of the core DISARM complex, DrmAB, both alone and in complex with an unmethylated phage DNA mimetic. These structures reveal that DrmAB core complex is autoinhibited by a trigger loop (TL) within DrmA and binding to DNA substrates containing a 5′ overhang dislodges the TL, initiating a long-range structural rearrangement for DrmAB activation. Together with structure-guided in vivo studies, our work provides insights into the mechanism of phage DNA recognition and specific activation of this widespread antiviral defense system.doi.org/10.1038/s41467-022-30673-1 - 2022

Four propargyl O-glycosides derivatized with mannose, glucose, and fructose moieties were synthesized and then incorporated within a diiron structure as part of a vinyliminium ligand. Hence, six glycoconjugated diiron complexes, [2−5]CF3SO3 (see Scheme 1) and the nonglycosylated analogues [6a−b]CF3SO3, were obtained in high yields and unambiguously characterized by elemental analysis, mass spectrometry, and IR and multinuclear NMR spectroscopies. All compounds exhibited a significant stability in DMSO-d6/D2O solution, with 63−89% of the complexes unaltered after 72 h at 37 °C and also in the cell culture medium. The cytotoxicity of [2−6]CF3SO3, as well as that of previously reported 7 and 8, was assessed on CT26 (mouse colon carcinoma), U87 (human glioblastoma), MCF-7 (human breast adenocarcinoma), and RPE-1 (human normal retina pigmented epithelium) cell lines. In general, the IC50 values correlate with the hydrophobicity of the compounds (measured as octanol−water partition coefficients) and do not show an appreciable level of selectivity against cancer cells with respect to the nontumor ones.doi.org/10.1021/acs.organomet.1c00519 - 2022

Photophysical investigations of the canonical nucleobases that make up DNA and RNA during the past 15 years have revealed that excited states formed by the absorption of UV radiation decay with subpicosecond lifetimes (i.e., o10􏰁12 s). Ultrashort lifetimes are a general property of absorbing sunscreen molecules, suggesting that the nucleobases are molecular survivors of a harsh UV environment. Encoding the genome using photostable building blocks is an elegant solution to the threat of photochemical damage. Ultrafast excited-state deactivation strongly supports the hypothesis that UV radiation played a major role in shaping molecular inventories on the early Earth before the emergence of life and the subsequent development of a protective ozone shield. Here, we review the general physical and chemical principles that underlie the photostability, or ‘‘UV hardiness’’, of modern nucleic acids and discuss the possible implications of these findings for prebiotic chemical evolution. In RNA and DNA strands, much longer-lived excited states are observed, which at first glance appear to increase the risk of photo-chemistry. It is proposed that the dramatically different photoproperties that emerge from assemblies of photostable building blocks may explain the transition from a world of molecular survival to a world in which energy-rich excited electronic states were eventually tamed for biological purposes such as energy transduction, signaling, and repair of the genetic machinery. - DOI: 10.1039/c6cp04230a - 2016

The notion of using synthetic heterocycles instead of the native bases to interface with DNA and RNA has been explored for nearly 60 years. Unnatural bases compatible with the DNA/RNA coding interface have the potential to expand the genetic code and co-opt the machinery of biology to access new macromolecular function; accordingly, this body of research is core to synthetic biology. While much of the literature on artificial bases focuses on code expansion, there is a significant and grow- ing effort on docking synthetic heterocycles to noncoding nucleic acid interfaces; this approach seeks to illuminate major processes of nucleic acids, including regulation of transcription, translation, transport, and transcript lifetimes. These major avenues of research at the coding and noncoding interfaces have in common fundamental principles in molecular recognition. Herein, we provide an overview of foundational literature in biophysics of base recognition and unnatural bases in coding to provide context for the developing area of targeting noncoding nucleic acid interfaces with synthetic bases, with a focus on systems developed through iterative design and biophysical study.

There are limited studies that investigate microneedling as a monotherapy for hair loss since majority of the trials combine it with other therapies such as topical minoxidil or platelet-rich plasma. While preliminary results look promising, further investigation of microneedling as a monotherapy in larger, randomized controlled trials will help determine its safety and efficacy, and place in treating Androgenic Alopecia. - DOI: 10.1111/jocd.14525 - 2021

Next generation sequencing (NGS) has made great strides in sequencing technology as it enables sequencing of genes in a high throughput manner with low cost. Various NGS platforms such as Illumina, Roche, ABI/SOLiD are used for wet-lab analysis of NGS data and computational tools such as BWA, Bowtie, Galaxy, SanGeniX are used for dry-lab analysis of NGS data. One of the important aspects of NGS data is its usage in early disease diagnosis especially in cancer which was earlier not possible with conventional sequencing technologies such as Sanger sequencing, NGS can identify all those mutations which cannot be identified using conventional sequencing technologies as researchers can now sequence the whole genome, exome or transcriptome. Exome sequencing is preferred, as a higher number of mutations are found to exist in the exome part of genes. The present comprehensive review encompasses the complete NGS data analysis workflow that includes alignment of NGS reads, identification and annotation of mutations and visualization, discussion of software tools for variant identification and annotation, evaluation of structural variation in NGS data, and study of different DNA sequencing technologies. In the field of clinical oncology, NGS has already proven its usefulness, and the mortality rate has been reduced, as now doctors can suggest a proper treatment to their patients by checking the complete genomic profile. However, data storage and the complexity in interpreting enormous amounts of data obtained with NGS still remain a computational challenge to researchers, as for each sample, the number of different and very large analysis files are generated directly from the raw sequence read file to the final result file. NGS resultant data is very complex, and its interpretation requires expert bioinformatics assistance, as a large number of mutations are identified from samples, but to differentiate clinically significant mutations among them with appropriate use of validation methods is a challenging task. This review is intended to provide researchers with a complete overview of NGS along with knowledge of how the tools will be employed, and insight into identification and interpretation of cancer mutations for clinical diagnostics. - doi.org/10.1016/j.imu.2018.05.003 - 2018

Mass spectrometry (MS)-based proteomics is the most comprehensive approach for the quantitative profiling of proteins, their interactions and modifications. It is a challenging topic as a firm grasp requires expertise in biochemistry for sample preparation, analytical chemistry for instrumentation and computational biology for data analysis. In this short guide, we highlight the various components of a mass spectrometer, the sample preparation process for conversion of proteins into peptides, and quantification and analysis strategies. The advancing technology of MS-based proteomics now opens up opportunities in clinical applications and single-cell analysis. - doi.org/10.1042/BIO20200057 - 2020

Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term. - doi.org/10.1186/s13073-020-00791-w - 2020

Despite evidence that deleterious variants in the same genes are implicated across multiple neurodevelopmental and neuropsychiatric disorders, there has been considerable interest in identifying genes that, when mutated, confer risk that is largely specific for autism spectrum disorder (ASD). Here, we review the findings and limitations of recent efforts to identify relatively ‘‘autism-specific’’ genes, efforts which focus on rare variants of large effect size that are thought to account for the observed phenotypes. We present a divergent interpretation of published evidence; discuss practical and theoretical issues related to studying the relationships between rare, large-effect deleterious variants and neurodevelopmental phenotypes; and describe potential future directions of this research. We argue that there is currently insufficient evidence to establish meaningful ASD specificity of any genes based on large-effect rare-variant data. - doi.org/10.1016/j.ajhg.2020.04.004 - 2020

Aptamers that bind non-fluorescent dyes and increase their fluorescence can be converted to fluorescent sensors. Here, we discuss and provide guidance for the design of split (binary) light up aptameric sensors (SLAS) for nucleic acid analysis. SLAS consist of two RNA or DNA strands and a fluorogenic organic dye added as a buffer component. The two strands hybridize to the analyzed DNA or RNA sequence and form a dye-binding pocket, followed by dye binding, and increase in its fluorescence. SLAS can detect nucleic acids in a cost-efficient label-free format since it does not require conjugation of organic dyes with nucleic acids. SLAS design is preferable over monolith fluorescent sensors due to simpler assay optimization and improved selectivity. RNA-based SLAS can be expressed in cells and used for intracellular monitoring and imaging biological molecules.

With the ability to resolve structures of macromolecules at atomic resolution, X-ray crystallography has been the most powerful tool in modern structural biology. At the same time, recent technical improvements have triggered a resolution revolution in the single-particle cryo-EM method. While the two methods are different in many respects, from sample preparation to structure determination, they both have the power to solve macromolecular structures at atomic resolution. It is important to understand the unique advantages and caveats of the two methods in solving structures and to appreciate the complementary nature of the two methods in structural biology. In this review we provide some examples, and discuss how X-ray crystallography and cryo-EM can be combined in deciphering structures of macromolecules for our full understanding of their biological mechanisms.- DOI: 10.1002/pro.3022 - 2016

Knowledge representation and reasoning (KR&R) has been successfully imple- mented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article, we describe concrete uses of Scalable PrecisiOn Medicine Knowledge Engine (SPOKE), an open knowledge network that connects curated information from thirty-seven specialized and human- curated databases into a single property graph, with 3 million nodes and 15 mil- lion edges to date. Applications discussed in this article include drug discovery, COVID-19 research and chronic disease diagnosis, and management. - DOI: 10.1002/aaai.12037 - 2021

Although DNA and RNA sequencing has a history spanning five decades, large-scale massively parallel sequencing, or next-generation sequencing (NGS), has only been commercially available for about 10 years. Nonetheless, the meteoric increase in sequencing throughput with NGS has dramatically changed our understanding of our genome and our- selves. Sequencing the first human genome as a haploid reference took nearly 10 years but now a full diploid human genome sequence can be accomplished in just a few days. NGS has also reduced the cost of generating sequence data and a plethora of sequence-based methods for probing a genome have emerged using NGS as the readout and have been applied to many species. NGS methods have also entered the medical realm and will see increasing use in diagnosis and treatment. NGS has largely been driven by short-read generation (150 bp) but new platforms have emerged and are now capable of generating long multikilobase reads. These latter platforms enable reference-independent genome assemblies and long-range haplotype generation. Rapid DNA and RNA sequencing is now mainstream and will continue to have an increasing impact on biology and medicine. - oi: 10.1101/cshperspect.a036798 - 2019

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a consensus approach, METEORE (https://github.com/comprna/METEORE), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets. - doi.org/10.1038/s41467-021-23778-6 - 2021

Human immunodeficiency virus (HIV-1) remains a major health threat. Viral capsid uncoating and nuclear import of the viral genome are critical for productive infection. The size of the HIV-1 capsid is generally believed to exceed the diameter of the nuclear pore complex (NPC), indicating that capsid uncoating has to occur prior to nuclear import. Here, we combined correlative light and electron microscopy with subtomogram averaging to capture the structural status of reverse transcription-competent HIV-1 complexes in infected T cells. We demonstrated that the diameter of the NPC in cellulo is sufficient for the import of apparently intact, cone-shaped capsids. Subsequent to nuclear import, we detected disrupted and empty capsid fragments, indicating that uncoating of the replication complex occurs by breaking the capsid open, and not by disassembly into individual subunits. Our data directly visualize a key step in HIV-1 replication and enhance our mechanistic understanding of the viral life cycle. - doi.org/10.1016/j.cell.2021.01.025 - 2021

The definition of epigenetics refers that molecular modifications on DNA that can regulate gene activity are independent of DNA sequence and mitotically stable. Notably, epigenetics studies have grown exponentially in the past few years. Recent progresses that lead to exciting discoveries and groundbreaking nature of this area demand thorough methodologies and advanced technologies to move epigenetics to the forefront of molecular biology. The most recognized epigenetic regulations are DNA methylation, histone modifications, and non-coding RNAs (ncRNAs). This review will discuss the modern techniques that are available to detect locus-specific and genome-wide changes for all epigenetic codes. Furthermore, updated analysis of technologies, newly developed methods, recent breakthroughs and bioinformatics pipelines in epigenetic analysis will be presented. These methods, as well as many others presented in this specific issue, provide comprehensive guidelines in the area of epigenetics that facilitate further developments in this promising and rapidly developing field. - doi.org/10.1016/j.ymeth.2020.06.022 - 2020

Chimeric antigen receptor (CAR) T‐cell therapy has dramatically shifted the landscape of treatment for lymphoid malignancies, especially diffuse large B‐cell lymphoma (DLBCL) and acute lymphoblastic leukemia (ALL). However, there continue to be significant limitations of this therapy, such as incomplete or nonsustained responses and severe toxicities in a subset of patients. Furthermore, expanding the role of CAR T‐cell therapy to new disease types is an important next step. In this review, we will highlight landmark trials for anti‐CD19 CAR T cells and first‐in‐human trials of novel CARs, as well as discuss promising innovative CAR designs that are still undergoing preclinical development. Lastly, we will discuss toxicity and mechanisms of CAR T‐cell resistance and failure, as well as potential future treatment approaches to these common issues. - DOI: 10.1002/hon.2591 - 2019

As RNA-binding proteins (RBPs) play essential roles in cellular physiology by interacting with target RNA molecules, binding site identification by UV crosslinking and immunoprecipitation (CLIP) of ribonucleoprotein complexes is critical to understanding RBP function. However, current CLIP protocols are technically demanding and yield low-complexity libraries with high experimental failure rates. We have developed an enhanced CLIP (eCLIP) protocol that decreases requisite amplification by ∼1,000-fold, decreasing discarded PCR duplicate reads by ∼60% while maintaining single-nucleotide binding resolution. By simplifying the generation of paired IgG and size-matched input controls, eCLIP improves specificity in the discovery of authentic binding sites. We generated 102 eCLIP experiments for 73 diverse RBPs in HepG2 and K562 cells (available at https://www.encodeproject.org), demonstrating that eCLIP enables large-scale and robust profiling, with amplification and sample requirements similar to those of ChIP-seq. eCLIP enables integrative analysis of diverse RBPs to reveal factor-specific profiles, common artifacts for CLIP and RNA-centric perspectives on RBP activity. - DOI: 10.1038/nmeth.3810 - 2016

The development of real-life applicable ion sensors, in particular those capable of repeat use and long-term monitoring, remains a formidable challenge. Herein, we demonstrate, in a proof-of-concept, the real-time voltammet- ric sensing of anions under continuous flow in a 3D-printed microfluidic system. Electro-active anion receptive halogen bonding (XB) and hydrogen bonding (HB) ferrocene-isophtha- lamide-(iodo)triazole films were employed as exemplary sensory interfaces. Upon exposure to anions, the cathodic perturbations of the ferrocene redox-transducer are monitored by repeat square-wave voltammetry (SWV) cycling and peak fitting of the voltammograms by a custom-written MATLAB script. This enables the facile and automated data processing of thousands of SW scans and is associated with an over one order-of-magnitude improvement in limits of detection. In addition, this improved analysis enables tuning of the measurement parameters such that high temporal resolution can be achieved. More generally, this new flow methodology is extendable to a variety of other analytes, including cations, and presents an important step towards translation of voltammetric ion sensors from laboratory to real-world applications. - doi.org/10.1002/chem.202103249 - 2021

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)—a blind assessment of the state of the field—AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined. - doi.org/10.1038/s41586-019-1923-7 - 2020

Structural biology is the study of the molecular architecture of proteins and nucleic acids, which are the basis for all life forms. Knowledge of these structures alone is not enough to understand their functions, but it has become clear that a detailed mechanistic picture of function is not possible without structural information. Studying structure can reveal how molecules have evolved, and this type of insight would otherwise be lost by looking at only the molecule’s sequence. - .doi.org/10.1016/j.bpj.2016.02.001 - 2016

Growth hormone–secreting (GH-secreting) pituitary tumors are driven by oncogenes that induce cAMP signaling. In this issue of the JCI, Ben-Shlomo et al. performed a whole-exome study of pituitary adenomas. GH-secreting tumors had a high frequency of whole chromosome or chromosome arm copy number alterations and were associated with an increase in the tumor protein p53 and the cyclin-dependent kinase inhibitor p21WAF1/CIP1, which are findings consistent with induction of a response to DNA damage. Further, treatment of mouse pituitary cells with cAMP pathway agonists in vitro and in vivo elicited biomarkers of DNA replication stress or double-strand breaks. The findings of Ben Shlomo et al. indicate that oncoproteins that drive constitutively high cAMP signaling pathway output in susceptible cell types can elicit DNA replication stress and may promote genomic instability. - doi.org/10.1172/JCI142237. - 2020

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’—has been an important open research problem for more than 50 years9. Despite recent progress existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14), demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. - doi.org/10.1038/s41586-021-03819-2 - 2021

Liquid-electron microscopy (EM), the room-temperature correlate to cryo-EM, is a rapidly growing field providing high-resolution insights of macromolecules in solution. Here, we describe how liquid-EM experiments can incorporate automated tools to propel the field to new heights. We demonstrate fresh workflows for specimen preparation, data collection, and computing processes to assess biological structures in liquid. Adeno-associated virus (AAV) and the SARS-CoV-2 nucleocapsid (N) were used as model systems to highlight the technical advances. These complexes were selected based on their major differences in size and natural symmetry. AAV is a highly symmetric, icosahedral assembly with a particle diameter of ∼25 nm. At the other end of the spectrum, N protein is an asymmetric monomer or dimer with dimensions of approximately 5–7 nm, depending upon its oligomerization state. Equally important, both AAV and N protein are popular subjects in biomedical research due to their high value in vaccine development and therapeutic efforts against COVID-19. Overall, we demonstrate how automated practices in liquid-EM can be used to decode molecules of interest for human health and disease. - doi:10.1017/S1431927621013921 - 2022

Cellular reprogramming can manipulate the identity of cells to generate the desired cell types1–3. The use of cell intrinsic components, including oocyte cytoplasm and transcription factors, can enforce somatic cell reprogramming to pluripotent stem cells4–7. By contrast, chemical stimulation by exposure to small molecules offers an alternative approach that can manipulate cell fate in a simple and highly controllable manner8–10. However, human somatic cells are refractory to chemical stimulation owing to their stable epigenome2,11,12 and reduced plasticity13,14; it is therefore challenging to induce human pluripotent stem cells by chemical reprogramming. Here we demonstrate, by creating an intermediate plastic state, the chemical reprogramming of human somatic cells to human chemically induced pluripotent stem cells that exhibit key features of embryonic stem cells. The whole chemical reprogramming trajectory analysis delineated the induction of the intermediate plastic state at the early stage, during which chemical-induced dedifferentiation occurred, and this process was similar to the dedifferentiation process that occurs in axolotl limb regeneration. Moreover, we identified the JNK pathway as a major barrier to chemical reprogramming, the inhibition of which was indispensable for inducing cell plasticity and a regeneration-like program by suppressing pro-inflammatory pathways. Our chemical approach provides a platform for the generation and application of human pluripotent stem cells in biomedicine. This study lays foundations for developing regenerative therapeutic strategies that use well-defined chemicals to change cell fates in humans. - doi.org/10.1038/s41586-022-04593-5 - 2022

The hallmarks of cancer conceptualization is a heuristic tool for distilling the vast complexity of cancer phenotypes and genotypes into a provisional set of underlying principles. As knowledge of cancer mechanisms has progressed, other facets of the disease have emerged as potential refinements. Herein, the prospect is raised that phenotypic plasticity and disrupted differentiation is a discrete hallmark capability, and that nonmutational epigenetic reprogram- ming and polymorphic microbiomes both constitute distinctive enabling characteristics that facilitate the acquisition of hallmark capabilities. Additionally, senescent cells, of varying origins, may be added to the roster of functionally important cell types in the tumor microenvironment. - doi: 10.1158/2159-8290.CD-21-1059 - 2022

The development of metastatic disease is a complex interplay of genetic and epigenetic factors from the host and cancer cells acting in a patient-specific manner. Inhibiting key driver traits of metastasis should yield survival benefit at any stage of the disease, and we look forward to the next generation of personalized medicines for cancer therapy that target cancer cell motility for increased therapeutic efficacy. - doi.org/10.1080/14737140.2020.1718496 - 2020

Brain imaging, specifically magnetic resonance imaging (MRI), plays a key role in the clinical and research aspects of neuro-oncology. Novel neuroimaging techniques enable the transformation of a brain MRI into a so-called average brain. This allows projects using already acquired brain MRIs to perform group analyses and draw conclusions. Once the data are in this average brain, several types of analyses can be performed. For example, determining the most vulnerable locations for certain tumor types or perhaps even the underlying circuitry and gene expression that might cause predisposition to tumor growth. This information may further our understanding of tumor behavior, leading to better patient counseling, surgery timing, and treatment monitoring. - doi.org/10.3390/ cancers14030464 - 2022

Mutations in Dystrophin, one of the largest proteins in the mammalian body, are causative for a severe form of muscle disease, Duchenne Muscular Dystrophy (DMD), affecting not only skeletal muscle, but also the heart. In particular, exons 45–52 constitute a hotspot for DMD mutations. A variety of molecular therapies have been developed, comprising vectors encoding micro-and minidystrophins as well as utrophin, a protein with partially overlapping functions. With the advent of the CRISPR-Cas9-nuclease, genome editing offers a novel option of correction of the disease-causing mutations. Full restoration of the healthy gene by homology directed repair is a rare event. However, non-homologous end-joining (NHEJ) may restore the reading frame by causing exon excision. This approach has first been demonstrated in mice and then translated to large animals (dogs, pigs). This review discusses the potential opportunities and limitations of genome editing in DMD, including the generation of appropriate animal models as well as new developments in genome editing tools. - doi.org/10.1038/s41434-021-00222-4 - 2021

RNA-containing structures, including ribonucleotide insertions, DNA:RNA hybrids and R-loops, have recently emerged as critical players in the maintenance of genome integrity. Strikingly, different enzymatic activities classically involved in genome maintenance contribute to their generation, their processing into genotoxic or repair intermediates, or their removal. Here we review how this substrate promiscuity can account for the detrimental and beneficial impacts of RNA insertions during genome metabolism. We summarize how in vivo and in vitro experiments support the contribution of DNA polymerases and homologous recombination proteins in the formation of RNA-containing structures, and we discuss the role of DNA repair enzymes in their removal. The diversity of pathways that are thus affected by RNA insertions likely reflects the ancestral function of RNA molecules in genome maintenance and transmission.

Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-based technology has revolutionized the field of biomedicine with broad applications in genome editing, therapeutics and diagnostics. While a majority of applications involve the RNA-guided site-specific DNA or RNA cleavage by CRISPR enzymes, recent successes in nucleic acid detection rely on their collateral and non-specific cleavage activated by viral DNA or RNA. Ranging in enzyme composition, the mechanism for distinguishing self- from foreign-nucleic acids, the usage of second messengers, and enzymology, the CRISPR enzymes provide a diverse set of diagnosis tools in further innovations. Structural biology plays an important role in elucidating the mechanisms of these CRISPR enzymes. Here we summarize and compare structures of three types of CRISPR enzymes used in nucleic acid detection captured in their respective functional forms and illustrate the current understanding of their activation mechanism. - doi:10.1016/j.jsb.2022.107838 - 2022

Despite the abundance of available software tools, optimal particle selection is still a vital issue in single-particle cryoelectron microscopy (cryo-EM). Regardless of the method used, most pickers struggle when ice thickness varies on a micrograph. IceBreaker allows users to estimate the relative ice gradient and flatten it by equalizing the local contrast. It allows the differentiation of particles from the background and improves overall particle picking performance. Furthermore, we introduce an additional parameter corresponding to local ice thickness for each particle. Particles with a defined ice thickness can be grouped and filtered based on this parameter during processing. These functionalities are especially valuable for on-the-fly processing to automatically pick as many particles as possible from each micrograph and to select optimal regions for data collection. Finally, estimated ice gradient distributions can be stored separately and used to inspect the quality of prepared samples. - doi.org/10.1016/j.str.2022.01.005 - 2022

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. - doi.org/10.1038/s41586-022-04554-y - 2022

Hyperglycemia is associated with poor clinical outcomes in critically ill patients. Initial clinical trials of intensive insulin therapy targeting blood glucose levels of 80 to 110 mg/dL showed improved outcomes, but subsequent trials found no benefits and even increased harm with this approach. Emerging literature has evaluated other glycemic indices including time-in-target blood glucose range, glycemic variability, and stress hyperglycemia ratio. These indices, while well described in observational studies, have not been addressed in the initial trials. Additionally, the patient’s preexisting diabetes status and preadmission diabetic control may modulate the outcomes of stringent glycemic control, with worse outcomes of hyperglycemia being observed in patients without diabetes and in those with well-controlled diabetes. Most medical societies recommend less stringent glucose control in the range of 140 to 180 mg/dL for critically ill patients. - doi:10.3949/ccjm.89a.20171 - 2022

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion–base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.- DOI: 10.1126/science.abj6987 - 2022

This article documents a keynote seminar presented at the IUCr Congress in Prague, 2021. The cryo-EM method microcrystal electron diffraction is described and put in the context of macromolecular electron crystallography from its origins in 2D crystals of membrane proteins to today’s application to 3D crystals a millionth the size of that needed for X-ray crystallography. Milestones in method development and applications are described with an outlook to the future. - doi.org/10.1107/S2052252521013063 - 2022

Pancreatic cancer is the third leading cause of cancer mortality in the United States, recently surpassing breast cancer. A key component of pancreatic cancer’s lethality is its acquired immune privilege, which is driven by an immunosuppressive microenvironment, poor T-cell infiltration, and a low mutational burden. Although immunotherapies such as checkpoint blockade or engineered T cells have yet to demonstrate efficacy, a growing body of evidence suggests that orthogonal combinations of these and other strategies could unlock immunotherapy in pancreatic cancer. In this review, we will discuss promising immunotherapies currently under investigation in pancreatic cancer and provide a roadmap for the development of prevention vaccines for this and other cancers. - doi:10.1016/j.trecan.2018.04.001 - 2018

Radiotherapy is a cornerstone of both curative and palliative cancer care. However, radiotherapy is severely limited by radiation-induced toxicities. If these toxicities could be reduced, a greater dose of radiation could be given therefore facilitating a better tumor response. Initial pre-clinical studies have shown that irradiation at dose rates far exceeding those currently used in clinical contexts reduce radiation-induced toxicities whilst maintaining an equivalent tumor response. This is known as the FLASH effect. To date, a single patient has been subjected to FLASH radiotherapy for the treatment of subcutaneous T-cell lymphoma resulting in complete response and minimal toxicities. The mechanism responsible for reduced tissue toxicity following FLASH radiotherapy is yet to be elucidated, but the most prominent hypothesis so far proposed is that acute oxygen depletion occurs within the irradiated tissue. This review examines the tissue response to FLASH radiotherapy, critically evaluates the evidence supporting hypotheses surrounding the biological basis of the FLASH effect, and considers the potential for FLASH radiotherapy to be translated into clinical contexts. - doi: 10.3389/fonc.2019.01563 - 2020

Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure1. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold2, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective.

Lithium is the most effective mood stabilizer for the treatment of bipolar disorder, but it is toxic at only twice the therapeutic dosage and has many undesirable side effects. It is likely that a small molecule could be found with lithium-like efficacy but without toxicity through target-based drug discovery; however, therapeutic target of lithium remains equivocal. Inositol monophosphatase is a possible target but no bioavailable inhibitors exist. Here we report that the antioxidant ebselen inhibits inositol monophosphatase and induces lithium-like effects on mouse behaviour, which are reversed with inositol, consistent with a mechanism involving inhibition of inositol recycling. Ebselen is part of the National Institutes of Health Clinical Collection, a chemical library of bioavailable drugs considered clinically safe but without proven use. Therefore, ebselen represents a lithium mimetic with the potential both to validate inositol monophosphatase inhibition as a treatment for bipolar disorder and to serve as a treatment itself. - DOI: 10.1038/ncomms2320 - 2013