Structural insights into the assembly pathway of the Helicobacter pylori CagT4SS outer membrane core complex.

Cag type IV secretion system (CagT4SS) translocates oncoprotein cytotoxin-associated gene A (CagA) into host cells and plays a key role in the pathogenesis of Helicobacter pylori. The structure of the outer membrane core complex (OMCC) in CagT4SS consists of CagX, CagY, CagM, CagT, and Cag3 in a stoichiometric ratio of 1:1:2:2:5 with 14-fold symmetry. However, the assembly pathway of OMCC remains elusive. Here, we report the crystal structures of CagT and Cag3-CagT complex, and the structural dynamics of Cag3 and CagT using hydrogen deuterium exchange-mass spectrometry (HDX-MS). The interwoven interaction of Cag3 and CagT involves conformational changes of CagT and ß strand swapping. In conjunction with biochemical and biophysical assays, we further demonstrate the different oligomerization states of Cag3 and Cag3-CagT complex. Additionally, the association with CagM requires the pre-formation of Cag3-CagT complex. These results demonstrate the generation of different intermediate sub-assemblies and their structural flexibility, potentially representing different building blocks for OMCC assembly.

Light-Activated Nanodiamond-Based Drug Delivery Systems for Spatiotemporal Release of Antisense Oligonucleotides.

Nanodiamonds (NDs) are considered promising delivery platforms, but inaccurate and uncontrolled release of drugs at target sites is the biggest challenge of NDs in precision medicine. This study presents the development of phototriggerable ND-based drug delivery systems, utilizing ortho-nitrobenzyl (o-NB) molecules as photocleavable linkers between drugs and nanocarriers. UV irradiation specifically cleaved o-NB molecules and then was followed by releasing antisense oligonucleotides from ND-based carriers in both buffer and cellular environments. This ND system carried cell nonpermeable therapeutic agents for bypassing lysosomal trapping and degradation. The presence of fluorescent nitrogen-vacancy centers also allowed NDs to serve as biological probes for tracing in cells. We successfully demonstrated phototriggered release of antisense oligonucleotides from ND-based nanocarriers, reactivating their antisense functions. This highlights the potential of NDs, photocleavable linkers, and light stimuli to create advanced drug delivery systems for controlled drug release in disease therapy, opening possibilities for targeted and personalized treatments.

Continuum of care in maternal and child health in Indonesia.

AIM: This paper aims to empirically analyze the socioeconomic and demographic correlates of maternal and child health (MCH) care utilization in Indonesia using the continuum of care (CoC) concept. BACKGROUND: The concept of CoC has emerged as an important guiding principle in reproductive, maternal, newborn, and child health. Indonesia's maternal mortality rate, neonatal mortality, and under-five mortality rates are among the highest in the Southeast Asian region. METHODS: Using pooled data from four successive waves of the nationally representative Indonesian Demographic and Health Survey (IDHS) conducted in the years 2002, 2007, 2012, and 2017, we use multivariate regression models to analyze care across four components of the continuum: antenatal care (ANC), institutional delivery, postnatal care for children, and full immunization (IM). FINDINGS: CoC at each stage of MCH care has improved continuously over the period 2002-2017 in Indonesia. Despite this, just less than one out of two children receive all four components of the CoC. The overall coverage of CoC from its second stage (four or more ANC visits) to the final stage (full child IM) is driven by the dropouts at the ANC visit stage, followed by the loss of postnatal checkups and child IM. We find that the probability of a child receiving CoC at each of the four stages is significantly associated with maternal age and education, the household's socioeconomic and demographic characteristics, and economic status. CONCLUSION: Complete CoC with improved, affordable, and accessible MCH care services has the potential to accelerate the progress of Sustainable Development Goal 3 by reducing maternal and childhood mortality risks. Our findings show that in Indonesia, the CoC continuously declines as women proceed from ANC to other MCH services, with a sharp decline observed after four ANC visits. Our study has identified key socioeconomic characteristics of women and children that increase their probability of failing to access care.

Accurate top protein variant discovery via low-N pick-and-validate machine learning.

A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein engineering. Toward this goal, we present a simple and effective machine learning-based strategy that outperforms other state-of-the-art methods. Our strategy integrates zero-shot prediction and multi-round sampling to direct active learning via experimenting with only a few predicted top variants. We find that four rounds of low-N pick-and-validate sampling of 12 variants for machine learning yielded the best accuracy of up to 92.6% in selecting the true top 1% variants in combinatorial mutant libraries, whereas two rounds of 24 variants can also be used. We demonstrate our strategy in successfully discovering high-performance protein variants from diverse families including the CRISPR-based genome editors, supporting its generalizable application for solving protein engineering tasks. A record of this paper's transparent peer review process is included in the supplemental information.

Ultra-stable threose nucleic acid-based biosensors for rapid and sensitive nucleic acid detection and in vivo imaging.

The human genome's nucleotide sequence variation, such as single nucleotide mutations, can cause numerous genetic diseases. However, detecting nucleic acids accurately and rapidly in complex biological samples remains a major challenge. While natural deoxyribonucleic acid (DNA) has been used as biorecognition probes, it has limitations like poor specificity, reproducibility, nuclease-induced enzymatic degradation, and reduced bioactivity on solid surfaces. To address these issues, we introduce a stable and reliable biosensor called graphene oxide (GO)- threose nucleic acid (TNA). It comprises chemically modified TNA capture probes on GO for detecting and imaging target nucleic acids in vitro and in vivo, distinguishing single nucleobase mismatches, and monitoring dynamic changes in target microRNA (miRNA). By loading TNA capture probes onto the GO substrate, the GO-TNA sensing platform for nucleic acid detection demonstrates a significant 88-fold improvement in the detection limit compared to TNA probes alone. This platform offers a straightforward preparation method without the need for costly and labor-intensive isolation procedures or complex chemical reactions, enabling real-time analysis. The stable TNA-based GO sensing nanoplatform holds promise for disease diagnosis, enabling rapid and accurate detection and imaging of various disease-related nucleic acid molecules at the in vivo level. STATEMENT OF SIGNIFICANCE: The study's significance lies in the development of the GO-TNA biosensor, which addresses limitations in nucleic acid detection. By utilizing chemically modified nucleic acid analogues, the biosensor offers improved reliability and specificity, distinguishing single nucleobase mismatches and avoiding false signals. Additionally, its ability to detect and image target nucleic acids in vivo facilitates studying disease mechanisms. The simplified preparation process enhances practicality and accessibility, enabling real-time analysis. The biosensor's potential applications extend beyond healthcare, contributing to environmental analysis and food safety. Overall, this study's findings have substantial implications for disease diagnosis, biomedical research, and diverse applications, advancing nucleic acid detection and its impact on various fields.

High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2.

Mapping mutations and discovering cellular determinants that cause the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce infected cells to form syncytia would facilitate the development of strategies for blocking the formation of such cell-cell fusion. Here we describe high-throughput screening methods based on droplet microfluidics and the size-exclusion selection of syncytia, coupled with large-scale mutagenesis and genome-wide knockout screening via clustered regularly interspaced short palindromic repeats (CRISPR), for the large-scale identification of determinants of cell-cell fusion. We used the methods to perform deep mutational scans in spike-presenting cells to pinpoint mutable syncytium-enhancing substitutions in two regions of the spike protein (the fusion peptide proximal region and the furin-cleavage site). We also used a genome-wide CRISPR screen in cells expressing the receptor angiotensin-converting enzyme 2 to identify inhibitors of clathrin-mediated endocytosis that impede syncytium formation, which we validated in hamsters infected with SARS-CoV-2. Finding genetic and cellular determinants of the formation of syncytia may reveal insights into the physiological and pathological consequences of cell-cell fusion.

Parallel engineering and activity profiling of a base editor system.

Selecting the most suitable existing base editors and engineering new variants for installing specific base conversions with maximal efficiency and minimal undesired edits are pivotal for precise genome editing applications. Here, we present a platform for creating and analyzing a library of engineered base editor variants to enable head-to-head evaluation of their editing performance at scale. Our comprehensive comparison provides quantitative measures on each variant's editing efficiency, purity, motif preference, and bias in generating single and multiple base conversions, while uncovering undesired higher indel generation rate and noncanonical base conversion for some of the existing base editors. In addition to engineering the base editor protein, we further applied this platform to investigate a hitherto underexplored engineering route and created guide RNA scaffold variants that augment the editor's base-editing activity. With the unknown performance and compatibility of the growing number of engineered parts including deaminase, CRISPR-Cas enzyme, and guide RNA scaffold variants for assembling the expanding collection of base editor systems, our platform addresses the unmet need for an unbiased, scalable method to benchmark their editing outcomes and accelerate the engineering of next-generation precise genome editors.

Versatile nanodiamond-based tools for therapeutics and bioimaging.

Nanodiamonds (NDs) are a remarkable class of carbon-based nanoparticles in nanomedicine which have recently become a hot topic of research due to their unique features including functionalization versatility, tunable opto-magnetic properties, chemical stability, minimal cytotoxicity, high affinity to biomolecules and biocompatibility. These attractive features make NDs versatile tools for a wide range of biologically relevant applications. In this feature article, we discuss the opto-magnetic properties of negatively charged nitrogen vacancy (NV-) centres in NDs as fluorescence probes. We further discuss the frequently used chemical methods for surface chemistry modification of NDs which are relevant for biomedical applications. The in vitro and in vivo biocompatibility of modified NDs is also highlighted. Subsequently, we give an overview of recent state-of-the-art biomedical applications of NDs as versatile tools for bioimaging and detection, and as targeting nanocarriers for chemotherapy, photodynamic therapy, gene therapy, antimicrobial and antiviral therapy, and bone tissue engineering. Finally, we pinpoint the main challenges for NDs in biomedical applications which lie ahead and discuss perspectives on future directions in advancing the field for practical applications and clinical translations.

In utero Ramadan exposure and child nutrition.

In this study, we empirically analyse whether in utero exposure to the Ramadan fasting period is negatively associated with child nutrition. The data for the analyses come from a retrospective assessment of 759,799 children from 103 Demographic and Health Surveys (DHS) across 56 countries during 2003-2020. Considering the month-long Ramadan exposure as a natural experiment, we implement an intent-to-treat framework, comparing stunting and underweight among children aged 0-5 years who were exposed to Ramadan fasting at any time in utero with those who were not exposed. Our findings do not show significant evidence to conclude that in utero exposure to the Ramadan fasting period is negatively associated with child nutrition. On the contrary, except for stunting in Muslim children who had in utero exposure to Ramadan fasting during the first months of pregnancy, we find no significant association between in utero exposure to Ramadan fasting and child stunting and underweight. Our main results are robust to multiple robustness checks.

Wavelength-Dependent, Orthogonal Photoregulation of DNA Liberation for Logic Operations.

In this study, we synthesized two phosphoramidites based on 2,7-bis-{4-nitro-8-[3-(2-propyl)-styryl]}-9,9-bis-[1-(3,6-dioxaheptyl)]-fluorene (BNSF) and 4,4'-bis-{8-[4-nitro-3-(2-propyl)-styryl]}-3,3'-di-methoxybiphenyl (BNSMB) structures as visible light-cleavable linkers for oligonucleotide conjugation. In addition to the commercial ultraviolet (UV) photocleavable (PC) linker, the BNSMB linker was further applied as a building component to construct photoregulated DNA devices as duplex structures, which are functionalized with fluorophores and quenchers. Selective cleavage of PC and BNSMB is achieved in response to ultraviolet (UV) and visible light irradiations as two inputs, respectively. This leads to controllable dissociation of pieces of DNA fragments, which is followed by changes of fluorescence emission as signal outputs of the system. By tuning the number and position of the photocleavable molecules, fluorophores, and quenchers, various DNA devices were developed, which mimic the functions of Boolean logic gates and achieve logic operations in AND, OR, NOR, and NAND gates in response to two different wavelengths of light inputs. By sequence design, the photolysis products can be precisely programmed in DNA devices and triggered to release in a selective and/or sequential manner. Thus, this photoregulated DNA device shows potential as a wavelength-dependent drug delivery system for selective control over the release of multiple individual therapeutic oligonucleotide-based drugs. We believe that our work not only enriches the library of photocleavable phosphoramidites available for bioconjugation but also paves the way for developing spatiotemporal-controlled, orthogonal-regulated DNA-based logic devices for a range of applications in materials science, polymers, chemistry, and biology.

Childhood immunization and age-appropriate vaccinations in Indonesia.

BACKGROUND: Childhood immunization is a cost-effective way to protect individuals against communicable diseases. However, although there is a large literature on childhood immunization in Indonesia, there is a paucity of research on the age-appropriateness on measles and DTwP-3 vaccination, and the inequities in immunization coverage across Indonesia. METHODS: In this paper, using seven waves of data from the nationally representative Indonesia Demographic and Health Surveys (DHS) covering the period 1991- 2017, we empirically analyse the socio-economic and demographic factors influencing the uptake of four routine vaccines (BCG, Polio-3, DTwP-3, and Measles). Specifically, using multivariate regression analysis, we identify the socio-economic and demographic factors influencing childhood immunization coverage. We further analyse the socio-economic and demographic correlates of the age-appropriateness of the measles and DTwP-3 vaccination coverage. RESULTS: Our findings show that parental education and use of healthcare services are strong predictors of full immunization and age-appropriate vaccinations. This study also finds evidence of spatial heterogeneity in both full immunization rates and age-appropriate vaccinations for measles and DTwP-3 vaccines. CONCLUSIONS: Our analysis finds that despite an improvement in the timing of vaccinations over the last two decades, a significant proportion of children continue to receive their measles and DTwP vaccinations age inappropriately. In particular, we find that maternal education and maternal engagement with healthcare services are critical in improving age appropriateness of vaccinations. From a policy perspective, these results call for concerted efforts by policy makers to address regional gaps in access to health services and immunization coverage, as well as to improve the age-appropriateness of vaccination.

Machine learning-coupled combinatorial mutagenesis enables resource-efficient engineering of CRISPR-Cas9 genome editor activities.

The genome-editing Cas9 protein uses multiple amino-acid residues to bind the target DNA. Considering only the residues in proximity to the target DNA as potential sites to optimise Cas9's activity, the number of combinatorial variants to screen through is too massive for a wet-lab experiment. Here we generate and cross-validate ten in silico and experimental datasets of multi-domain combinatorial mutagenesis libraries for Cas9 engineering, and demonstrate that a machine learning-coupled engineering approach reduces the experimental screening burden by as high as 95% while enriching top-performing variants by ∼7.5-fold in comparison to the null model. Using this approach and followed by structure-guided engineering, we identify the N888R/A889Q variant conferring increased editing activity on the protospacer adjacent motif-relaxed KKH variant of Cas9 nuclease from Staphylococcus aureus (KKH-SaCas9) and its derived base editor in human cells. Our work validates a readily applicable workflow to enable resource-efficient high-throughput engineering of genome editor's activity.

Nucleic Acids and Their Analogues for Biomedical Applications.

Nucleic acids are emerging as powerful and functional biomaterials due to their molecular recognition ability, programmability, and ease of synthesis and chemical modification. Various types of nucleic acids have been used as gene regulation tools or therapeutic agents for the treatment of human diseases with genetic disorders. Nucleic acids can also be used to develop sensing platforms for detecting ions, small molecules, proteins, and cells. Their performance can be improved through integration with other organic or inorganic nanomaterials. To further enhance their biological properties, various chemically modified nucleic acid analogues can be generated by modifying their phosphodiester backbone, sugar moiety, nucleobase, or combined sites. Alternatively, using nucleic acids as building blocks for self-assembly of highly ordered nanostructures would enhance their biological stability and cellular uptake efficiency. In this review, we will focus on the development and biomedical applications of structural and functional natural nucleic acids, as well as the chemically modified nucleic acid analogues over the past ten years. The recent progress in the development of functional nanomaterials based on self-assembled DNA-based platforms for gene regulation, biosensing, drug delivery, and therapy will also be presented. We will then summarize with a discussion on the advanced development of nucleic acid research, highlight some of the challenges faced and propose suggestions for further improvement.

High-fidelity KKH variant of Staphylococcus aureus Cas9 nucleases with improved base mismatch discrimination.

The Cas9 nuclease from Staphylococcus aureus (SaCas9) holds great potential for use in gene therapy, and variants with increased fidelity have been engineered. However, we find that existing variants have not reached the greatest accuracy to discriminate base mismatches and exhibited much reduced activity when their mutations were grafted onto the KKH mutant of SaCas9 for editing an expanded set of DNA targets. We performed structure-guided combinatorial mutagenesis to re-engineer KKH-SaCas9 with enhanced accuracy. We uncover that introducing a Y239H mutation on KKH-SaCas9's REC domain substantially reduces off-target edits while retaining high on-target activity when added to a set of mutations on REC and RuvC domains that lessen its interactions with the target DNA strand. The Y239H mutation is modelled to have removed an interaction from the REC domain with the guide RNA backbone in the guide RNA-DNA heteroduplex structure. We further confirmed the greatly improved genome-wide editing accuracy and single-base mismatch discrimination of our engineered variants, named KKH-SaCas9-SAV1 and SAV2, in human cells. In addition to generating broadly useful KKH-SaCas9 variants with unprecedented accuracy, our findings demonstrate the feasibility for multi-domain combinatorial mutagenesis on SaCas9's DNA- and guide RNA- interacting residues to optimize its editing fidelity.

A Combinatorial CRISPR-Cas9 Screen Identifies Ifenprodil as an Adjunct to Sorafenib for Liver Cancer Treatment.

Systematic testing of existing drugs and their combinations is an attractive strategy to exploit approved drugs for repurposing and identifying the best actionable treatment options. To expedite the search among many possible drug combinations, we designed a combinatorial CRISPR-Cas9 screen to inhibit druggable targets. Coblockade of the N-methyl-d-aspartate receptor (NMDAR) with targets of first-line kinase inhibitors reduced hepatocellular carcinoma (HCC) cell growth. Clinically, HCC patients with low NMDAR1 expression showed better survival. The clinically approved NMDAR antagonist ifenprodil synergized with sorafenib to induce the unfolded protein response, trigger cell-cycle arrest, downregulate genes associated with WNT signaling and stemness, and reduce self-renewal ability of HCC cells. In multiple HCC patient-derived organoids and human tumor xenograft models, the drug combination, but neither single drug alone, markedly reduced tumor-initiating cancer cell frequency. Because ifenprodil has an established safety history for its use as a vasodilator in humans, our findings support the repurposing of this drug as an adjunct for HCC treatment to improve clinical outcome and reduce tumor recurrence. These results also validate an approach for readily discovering actionable combinations for cancer therapy. SIGNIFICANCE: Combinatorial CRISPR-Cas9 screening identifies actionable targets for HCC therapy, uncovering the potential of combining the clinically approved drugs ifenprodil and sorafenib as a new effective treatment regimen.

Facilitating Machine Learning-Guided Protein Engineering with Smart Library Design and Massively Parallel Assays.

Protein design plays an important role in recent medical advances from antibody therapy to vaccine design. Typically, exhaustive mutational screens or directed evolution experiments are used for the identification of the best design or for improvements to the wild-type variant. Even with a high-throughput screening on pooled libraries and Next-Generation Sequencing to boost the scale of read-outs, surveying all the variants with combinatorial mutations for their empirical fitness scores is still of magnitudes beyond the capacity of existing experimental settings. To tackle this challenge, in-silico approaches using machine learning to predict the fitness of novel variants based on a subset of empirical measurements are now employed. These machine learning models turn out to be useful in many cases, with the premise that the experimentally determined fitness scores and the amino-acid descriptors of the models are informative. The machine learning models can guide the search for the highest fitness variants, resolve complex epistatic relationships, and highlight bio-physical rules for protein folding. Using machine learning-guided approaches, researchers can build more focused libraries, thus relieving themselves from labor-intensive screens and fast-tracking the optimization process. Here, we describe the current advances in massive-scale variant screens, and how machine learning and mutagenesis strategies can be integrated to accelerate protein engineering. More specifically, we examine strategies to make screens more economical, informative, and effective in discovery of useful variants.

Publisher Correction: Combinatorial mutagenesis en masse optimizes the genome editing activities of SpCas9.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Combinatorial mutagenesis en masse optimizes the genome editing activities of SpCas9.

The combined effect of multiple mutations on protein function is hard to predict; thus, the ability to functionally assess a vast number of protein sequence variants would be practically useful for protein engineering. Here we present a high-throughput platform that enables scalable assembly and parallel characterization of barcoded protein variants with combinatorial modifications. We demonstrate this platform, which we name CombiSEAL, by systematically characterizing a library of 948 combination mutants of the widely used Streptococcus pyogenes Cas9 (SpCas9) nuclease to optimize its genome-editing activity in human cells. The ease with which the editing activities of the pool of SpCas9 variants can be assessed at multiple on- and off-target sites accelerates the identification of optimized variants and facilitates the study of mutational epistasis. We successfully identify Opti-SpCas9, which possesses enhanced editing specificity without sacrificing potency and broad targeting range. This platform is broadly applicable for engineering proteins through combinatorial modifications en masse.

Assessing the benefits of horizontal gene transfer by laboratory evolution and genome sequencing.

BACKGROUND: Recombination is widespread across the tree of life, because it helps purge deleterious mutations and creates novel adaptive traits. In prokaryotes, it often takes the form of horizontal gene transfer from a donor to a recipient bacterium. While such transfer is widespread in natural communities, its immediate fitness benefits are usually unknown. We asked whether any such benefits depend on the environment, and on the identity of donor and recipient strains. To this end, we adapted Escherichia coli to two novel carbon sources over several hundred generations of laboratory evolution, exposing evolving populations to various DNA donors. RESULTS: At the end of these experiments, we measured fitness and sequenced the genomes of 65 clones from 34 replicate populations to study the genetic changes associated with adaptive evolution. Furthermore, we identified candidate de novo beneficial mutations. During adaptive evolution on the first carbon source, 4-Hydroxyphenylacetic acid (HPA), recombining populations adapted better, which was likely mediated by acquiring the hpa operon from the donor. In contrast, recombining populations did not adapt better to the second carbon source, butyric acid, even though they suffered fewer extinctions than non-recombining populations. The amount of DNA transferred, but not its benefit, strongly depended on the donor-recipient strain combination. CONCLUSIONS: To our knowledge, our study is the first to investigate the genomic consequences of prokaryotic recombination and horizontal gene transfer during laboratory evolution. It shows that the benefits of recombination strongly depend on the environment and the foreign DNA donor.