Focus 26 January 2021

Biotechnology and methods

Methodology development promotes science advancement. Application of new scientific discoveries to biological processes, organisms, or systems can help to sustainably produce products for healing, feeding, or fueling. This page showcases our recent publications that report methodological or biotechnological advances relevant to biological, biomedical, and agricultural sciences.

Featured articles

AI-driven high-throughput droplet screening of cell-free gene expression

Cell-free gene expression (CFE) systems are often constrained by numerous biochemical components required to maintain biocatalytic efficiency. Here, the authors propose a droplet-AI combined approach to perform high-throughput and efficient combinatorial screening of CFE. This work led to simplified CFE systems with improved yield and cost-effectiveness.
- Jiawei Zhu
- Yaru Meng
- Yifan Liu
ArticleOpen Access19 Mar 2025 Nature Communications
Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification

Studying cell polarity is often limited by the complexity and variety of image data. Polarity-JaM is a software suite streamlining cell polarity analysis with easy-to-use tools and interfaces demonstrated for endothelial cell behaviour.
- Wolfgang Giese
- Jan Philipp Albrecht
- Holger Gerhardt
ArticleOpen Access8 Feb 2025 Nature Communications
Systematic representation and optimization enable the inverse design of cross-species regulatory sequences in bacteria

Regulatory sequences encode crucial gene expression signals, but their functionality across species remains unclear. Here, the authors introduce DeepCROSS, an AI-aided strategy that utilises large-scale meta-representation and an accurate predictor for the inverse design of regulatory sequences.
- Pengcheng Zhang
- Qixiu Du
- Xiaowo Wang
ArticleOpen Access19 Feb 2025 Nature Communications
System- and sample-agnostic isotropic three-dimensional microscopy by weakly physics-informed, domain-shift-resistant axial deblurring

Three-dimensional imaging is crucial for biomedical research, yet microscopy faces axial resolution limitations. Here, authors introduce SSAI-3D that adapts training datasets and sparsely finetunes a network to achieve robust results across various biological samples and microscopy systems.
- Jiashu Han
- Kunzan Liu
- Sixian You
ArticleOpen Access16 Jan 2025 Nature Communications
Reliability of high-quantity human brain organoids for modeling microcephaly, glioma invasion and drug screening

Human brain organoids are plagued by heterogeneity and poor reproducibility, critical parameters for reliable disease modeling and drug testing. Here, the authors report on Hi-Q organoids which solve these limitations and can be cryopreserved in large quantities.
- Anand Ramani
- Giovanni Pasquini
- Jay Gopalakrishnan
ArticleOpen Access19 Dec 2024 Nature Communications
METASPACE-ML: Context-specific metabolite annotation for imaging mass spectrometry using machine learning

Imaging mass spectrometry has revolutionised spatial metabolomics, but metabolites are annotated for only a fraction of the data. Here, authors show that METASPACE-ML enhances precision, increases throughput, and improves the identification of low-intensity and biologically relevant metabolites.
- Bishoy Wadie
- Lachlan Stuart
- Theodore Alexandrov
ArticleOpen Access22 Oct 2024 Nature Communications
ChromaFold predicts the 3D contact map from single-cell chromatin accessibility

Obtaining a high-resolution contact map using current 3D genomics technologies can be challenging with small input cell numbers. Here, the authors develop ChromaFold, a deep learning model that predicts cell-type-specific 3D contact maps from single-cell chromatin accessibility data alone.
- Vianne R. Gao
- Rui Yang
- Christina S. Leslie
ArticleOpen Access1 Nov 2024 Nature Communications
Composite Hedges Nanopores codec system for rapid and portable DNA data readout with high INDEL-Correction

DNA is a promising medium for data storage but requires efficient sequencing methods for real-time data retrieval. Here, authors introduce Composite Hedges Nanopores (CHN), a nanopore-based codec scheme that improves sequencing efficiency and data accuracy, supporting real-time data retrieval.
- Xuyang Zhao
- Junyao Li
- Yi Li
ArticleOpen Access30 Oct 2024 Nature Communications
Highly efficient modeling and optimization of neural fiber responses to electrical stimulation

Electricity can be used to stimulate the nervous system to treat diseases, and computer models are powerful tools for designing these therapies. Here, authors develop a model of neurons’ responses to electricity that is accurate and thousands of times faster than the current industry standard.
- Minhaj A. Hussain
- Warren M. Grill
- Nicole A. Pelot
ArticleOpen Access31 Aug 2024 Nature Communications
Systematic identification of post-transcriptional regulatory modules

RNA binding proteins (RBPs) regulate various RNA processes, yet their interactions remain poorly understood. Here, authors generate a comprehensive map of RBP interactions using multimodal data, uncovering context-specific functions and revealing complex post-transcriptional regulatory networks.
- Matvei Khoroshkin
- Andrey Buyan
- Hani Goodarzi
ArticleOpen Access9 Sep 2024 Nature Communications
Efficient and reproducible generation of human iPSC-derived cardiomyocytes and cardiac organoids in stirred suspension systems

Human iPSC-CMs are invaluable for cardiac disease modeling and regeneration. Here, authors developed an optimized suspension culture protocol to efficiently and reproducibly differentiate hiPSCs into cardiomyocytes and cardiac organoids.
- Maksymilian Prondzynski
- Paul Berkson
- William T. Pu
ArticleOpen Access15 Jul 2024 Nature Communications
Graph Fourier transform for spatial omics representation and analyses of complex organs

SpaGFT is a spatial omics representation method. It identifies spatially variable genes, enhances gene imputation, detects immunological regions, and characterises variations in secondary lymphoid organs. This method improves predictive power in wide downstream machine-learning tasks.
- Yuzhou Chang
- Jixin Liu
- Qin Ma
ArticleOpen Access29 Aug 2024 Nature Communications
Accurate long-read transcript discovery and quantification at single-cell, pseudo-bulk and bulk resolution with Isosceles

Analysis of nanopore long-read sequencing is challenged by technical noise, particularly in single cells. Here, authors introduce Isosceles, a toolkit for accurate isoform detection, quantification, and flexible downstream analysis of long-read data at single-cell, pseudo-bulk and bulk resolutions.
- Michal Kabza
- Alexander Ritter
- Timothy Sterne-Weiler
ArticleOpen Access25 Aug 2024 Nature Communications
Evaluating batch correction methods for image-based cell profiling

Batch effects can limit the usefulness of image-based profiling data. Here, authors benchmark ten popular batch correction techniques on a large Cell Painting dataset, evaluating multiple metrics. They identify Harmony and Seurat RPCA as top methods across diverse complex scenarios.
- John Arevalo
- Ellen Su
- Shantanu Singh
ArticleOpen Access2 Aug 2024 Nature Communications
Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign

Comparative transcriptomics of whole brains across species is vital in neuroscience. Here, authors develop a deep learning method, BrainAlign, to align spatial transcriptomics across human and mouse brains. BrainAlign identifies conserved brain regions and uncovers similar patterns for marker genes.
- Biao Zhang
- Shuqin Zhang
- Shihua Zhang
ArticleOpen Access30 Jul 2024 Nature Communications
scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning

Single-cell sequencing is vital for studying complex diseases but is costly. Here, authors introduce scSemiProfiler, a deep generative learning framework that infers single-cell profiles by combining bulk sequencing with single-cell data from selected samples, offering a cost-effective solution.
- Jingtao Wang
- Gregory J. Fonseca
- Jun Ding
ArticleOpen Access16 Jul 2024 Nature Communications
A unified model-based framework for doublet or multiplet detection in single-cell multiomics data

Multiplets in single-cell sequencing can obscure true biological findings. Here, authors present COMPOSITE, a model-based multiplet detection framework, which helps prevent multiplet clusters, especially in single-cell multiomics data.
- Haoran Hu
- Xinjun Wang
- Wei Chen
ArticleOpen Access2 Jul 2024 Nature Communications
Germline Cas9 promoters with improved performance for homing gene drive

High-performance promoters are needed for gene drives; these are currently lacking in Drosophila melanogaster. Here the authors tested eleven Drosophila melanogaster germline promoters in several configurations and show higher drive conversion efficiency with minimal embryo resistance.
- Jie Du
- Weizhe Chen
- Jackson Champer
ArticleOpen Access29 May 2024 Nature Communications
A mechanical-assisted post-bioprinting strategy for challenging bone defects repair

Bioprinting has revitalized tissue regeneration efforts, yet challenges persist due to cell damage during fabrication and mechanical instability of printed scaffolds. Here, the authors develop a mechanical-assisted post-bioprinting strategy for loading cells into hollow scaffolds that effectively repair challenging bone defects.
- Jirong Yang
- Zhigang Chen
- Changshun Ruan
ArticleOpen Access26 Apr 2024 Nature Communications
Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry

Single-cell manipulation and processing techniques and improvements in mass spectrometry sensitivity make single-cell proteomic profiling feasible. This study presents a label-free approach for the characterisation of native N-glycans of single mammalian cells and ng-level blood isolates, demonstrating the potential to detect cell surface glycome changes at the single-cell level in health or disease.
- Anne-Lise Marie
- Yunfan Gao
- Alexander R. Ivanov
ArticleOpen Access8 May 2024 Nature Communications
De novo generation of multi-target compounds using deep generative chemistry

Polypharmacology drugs are compounds designed to inhibit multiple protein targets. Here, authors use recent advances in AI to rapidly generate polypharmacology compounds against any pair of protein targets, experimentally validating numerous compounds targeting MEK1 and mTOR.
- Brenton P. Munson
- Michael Chen
- Trey Ideker
ArticleOpen Access6 May 2024 Nature Communications
Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes

Metagenomic taxonomic profiling usually relies either on reads or assembled contigs/MAGs. Here, authors present RAT, a tool that integrates taxonomic signals from reads, contigs, and MAGs into one profile with high precision and sensitivity. RAT provides a comprehensive view of the microbiome.
- Ernestina Hauptfeld
- Nikolaos Pappas
- F. A. Bastiaan von Meijenfeldt
ArticleOpen Access20 Apr 2024 Nature Communications
Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy

Ultrasound localisation microscopy enables deep tissue microvascular imaging. Here, authors introduce LOCA-ULM, a deep learning pipeline enhancing localisation accuracy in high microbubble concentrations. LOCA-ULM reveals dense cerebrovascular networks and enhances the sensitivity of functional ULM.
- YiRang Shin
- Matthew R. Lowerison
- Pengfei Song
ArticleOpen Access4 Apr 2024 Nature Communications
A citric acid cycle-deficient Escherichia coli as an efficient chassis for aerobic fermentations

While tricarboxylic acid cycle (TCA cycle) is required for heterotrophic microbes, it reduces carbon yield of industrial products due to the release of excess CO2. Here, the authors construct an E. coli strain without a functional TCA cycle and demonstrate its feasibility as a chassis strain for production of four separate compounds.
- Hang Zhou
- Yiwen Zhang
- Baixue Lin
ArticleOpen Access15 Mar 2024 Nature Communications
Engineering intelligent chassis cells via recombinase-based MEMORY circuits

The unification of decision-making, communication, and memory would enable the programming of intelligent biotic systems. Here, the authors achieve this goal by engineering E. coli chassis cells with an array of inducible recombinases that mediate diverse genetic programs.
- Brian D. Huang
- Dowan Kim
- Corey J. Wilson
ArticleOpen Access18 Mar 2024 Nature Communications
Microinterfaces in biopolymer-based bicontinuous hydrogels guide rapid 3D cell migration

Extracellular microinterfaces provide cells with migration tracks in vivo. Here, the authors introduce these microtracks into bicontinuous hydrogels to elicit rapid cell migration in 3-dimensional contexts.
- Karen L. Xu
- Nikolas Di Caprio
- Jason A. Burdick
ArticleOpen Access29 Mar 2024 Nature Communications
Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance

RNA splicing serves as a critical layer of gene expression regulation. Here, authors introduce SCASL for investigating the heterogeneity of RNA splicing landscapes at single-cell resolution, offering a novel scheme for classifying cell identities with physiological relevance.
- Xianke Xiang
- Yao He
- Xuerui Yang
ArticleOpen Access9 Mar 2024 Nature Communications
Statistical method scDEED for detecting dubious 2D single-cell embeddings and optimizing t-SNE and UMAP hyperparameters

2D visualisation of single-cell data is highly impacted by the hyperparameter setting of the 2D embedding method, such as t-SNE and UMAP. Here, authors develop a statistical method scDEED to detect dubious cell embeddings and optimise the hyperparameter setting for trustworthy visualisation.
- Lucy Xia
- Christy Lee
- Jingyi Jessica Li
ArticleOpen Access26 Feb 2024 Nature Communications
Fudging the volcano-plot without dredging the data

Selecting omic biomarkers using both their effect size and their differential status significance (i.e., selecting the “volcano-plot outer spray”) has long been equally biologically relevant and statistically troublesome. However, recent proposals are paving the way to resolving this dilemma.
- Thomas Burger
CommentOpen Access15 Feb 2024 Nature Communications
Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit

Fungi have the potential to produce sustainable foods for a growing population, but current products are based on a small number of strains with inherent limitations. Here, the authors develop genetic tools for an edible fungus and engineer its nutritional value and sensory appeal for alternative meat applications.
- Vayu Maini Rekdal
- Casper R. B. van der Luijt
- Jay D. Keasling
ArticleOpen Access14 Mar 2024 Nature Communications
Advancing the scale of synthetic biology via cross-species transfer of cellular functions enabled by iModulon engraftment

Machine learning applied to large compendia of transcriptomic data has enabled the decomposition of bacterial transcriptomes to identify independently modulated sets of genes. Here the authors present iModulon-based engineering for precise identification of genes for cross-species function transfer to streamline synthetic biology for strain development and biomanufacturing.
- Donghui Choe
- Connor A. Olson
- Bernhard O. Palsson
ArticleOpen Access15 Mar 2024 Nature Communications
OrthoID: profiling dynamic proteomes through time and space using mutually orthogonal chemical tools

Proteomics at the organelle contact site remains challenging due to the spatial and temporal dynamics of proteins. Here, the authors developed OrthoID, a mutually orthogonal dual enzymatic proteomics approach to explore the proteome at the contact site of the endoplasmic reticulum and mitochondria.
- Ara Lee
- Gihyun Sung
- Kimoon Kim
ArticleOpen Access29 Feb 2024 Nature Communications
MAIVeSS: streamlined selection of antigenically matched, high-yield viruses for seasonal influenza vaccine production

Vaccines combat global influenza threats, relying on timely selection of optimal seed viruses. Here, authors introduce MAIVeSS, a machine learning assisted framework to streamline vaccine seed virus selection using genomic sequence, expediting seasonal flu vaccine production and supply.
- Cheng Gao
- Feng Wen
- Xiu-Feng Wan
ArticleOpen Access6 Feb 2024 Nature Communications
Semi-supervised integration of single-cell transcriptomics data

Batch effects hinder multi-sample single-cell data analyses. Here, authors present STACAS, a scalable single-cell RNA-seq data integration tool that uses prior cell type knowledge to preserve biological variability, demonstrating robustness to noisy input cell type labels.
- Massimo Andreatta
- Léonard Hérault
- Santiago J. Carmona
ArticleOpen Access29 Jan 2024 Nature Communications
SiFT: uncovering hidden biological processes by probabilistic filtering of single-cell data

Cells simultaneously encode multiple signals, some harder to recover. Here, authors introduce SiFT (Signal FilTering), a kernel-based projection method, revealing underlying biological processes in single-cell data.
- Zoe Piran
- Mor Nitzan
ArticleOpen Access26 Jan 2024 Nature Communications
Anti-correlated feature selection prevents false discovery of subpopulations in scRNAseq

Typical single-cell RNAseq pipelines will subcluster homogeneous cells. Here, authors present a computational algorithm for accurately identifying cell-type marker genes in single-cell data analysis with a low false discovery rate.
- Scott R. Tyler
- Daniel Lozano-Ojalvo
- Eric E. Schadt
ArticleOpen Access24 Jan 2024 Nature Communications
Rational strain design with minimal phenotype perturbation

No consensus exists on the computationally tractable use of dynamic models for strain design. To tackle this, the authors report a framework, nonlinear-dynamic-model-assisted rational metabolic engineering design, for efficiently designing robust, artificially engineered cellular organisms.
- Bharath Narayanan
- Daniel Weilandt
- Vassily Hatzimanikatis
ArticleOpen Access24 Jan 2024 Nature Communications
Compositional and temporal division of labor modulates mixed sugar fermentation by an engineered yeast consortium

Synthetic microbial communities are suitable for mixed substrates fermentation and long metabolic pathway engineering. Here, the authors combine fermentation experiments with mathematical modeling to reveal the effect of compositional and temporal changes on division of labor in cellulosic ethanol production using two yeast strains.
- Jonghyeok Shin
- Siqi Liao
- Yong-Su Jin
ArticleOpen Access26 Jan 2024 Nature Communications
A genetic circuit on a single DNA molecule as an autonomous dissipative nanodevice

Achieving genetic circuits on single DNA molecules could have varied applications. Here, authors observed proteins emerging from single DNA molecules through coupled transcription-translation complexes, and show that nascent proteins lingered on DNA, regulating cascaded reactions on the same DNA and allowing the design of a pulsatile genetic circuit.
- Ferdinand Greiss
- Nicolas Lardon
- Roy Bar-Ziv
ArticleOpen Access29 Jan 2024 Nature Communications
Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing

Utilising geometric information and reducing computational costs are key challenges in the molecular modelling field. Here, authors propose ViSNet, which efficiently extracts geometric features, accurately predicts molecular properties, and drives simulations with interpretability.
- Yusong Wang
- Tong Wang
- Tie-Yan Liu
ArticleOpen Access5 Jan 2024 Nature Communications
BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data

Subcellular in situ spatial transcriptomics offers the promise to address biological problems that were previously inaccessible but requires accurate cell segmentation to uncover insights. Here, authors present BIDCell, a biologically informed, deep learning-based cell segmentation framework.
- Xiaohang Fu
- Yingxin Lin
- Jean Y. H. Yang
ArticleOpen Access13 Jan 2024 Nature Communications
MarsGT: Multi-omics analysis for rare population inference using single-cell graph transformer

Identifying rare cell populations is key to understanding cancer progression and response to therapy. Here, authors introduce MarsGT, an end-to-end deep learning model for rare cell population identification from scMulti-omics data.
- Xiaoying Wang
- Maoteng Duan
- Qin Ma
ArticleOpen Access6 Jan 2024 Nature Communications
Derivation of human primordial germ cell-like cells in an embryonic-like culture

Derivation of human primordial germ cell-like cells (hPGCLCs) is critical for reproductive medicine. Here, authors report the induction of hPGCLCs in a bioengineered human pluripotent stem cell culture that mimics peri-implantation human development.
- Sajedeh Nasr Esfahani
- Yi Zheng
- Jianping Fu
ArticleOpen Access2 Jan 2024 Nature Communications
Reprogramming mechanism dissection and trophoblast replacement application in monkey somatic cell nuclear transfer

Somatic cloning of rhesus monkey has not been successful until now. Here, authors report epigenetic abnormalities in SCNT embryos and placentas and develop a trophoblast replacement method that enables them to successful clone of a healthy male rhesus monkey.
- Zhaodi Liao
- Jixiang Zhang
- Qiang Sun
ArticleOpen Access16 Jan 2024 Nature Communications
rworkflows: automating reproducible practices for the R community

Reproducibility is essential for the progress of research, yet achieving it remains elusive even in computational fields. Here, authors develop the rworkflows suite, making robust CI/CD workflows easy and freely accessible to all R package developers.
- Brian M. Schilder
- Alan E. Murphy
- Nathan G. Skene
ArticleOpen Access2 Jan 2024 Nature Communications
ECOLE: Learning to call copy number variants on whole exome sequencing data

Copy number variants (CNV) are shown to contribute to the etiology of various genetic disorders. Here, authors present ECOLE, a deep learning-based somatic and germline CNV caller for WES data. Utilising a variant of the transformer architecture, the model is trained to call CNVs per exon.
- Berk Mandiracioglu
- Furkan Ozden
- A. Ercument Cicek
ArticleOpen Access2 Jan 2024 Nature Communications
JOINTLY: interpretable joint clustering of single-cell transcriptomes

Batch integration is a critical yet challenging step in many single-cell RNA-seq analysis workflows. Here, authors present JOINTLY, a hybrid linear and non-linear NMF-based algorithm, providing interpretable and robust cell clustering against over-integration.
- Andreas Fønss Møller
- Jesper Grud Skat Madsen
ArticleOpen Access20 Dec 2023 Nature Communications
Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Deciphering the roles of gene regulation in cell fate decisions is crucial. Here, authors present CEFCON, a network-based framework that reveals cell-lineage-specific gene regulatory networks and identifies driver regulators controlling cell fate decisions from single-cell transcriptomics data.
- Peizhuo Wang
- Xiao Wen
- Jianyang Zeng
ArticleOpen Access20 Dec 2023 Nature Communications
STalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping

Spatial transcriptomics (ST) enables gene expression characterisation within tissue sections, but comparing across sections and technologies remains challenging. Here, authors develop STalign to spatially align ST data and demonstrate applications including aligning to common coordinate frameworks.
- Kalen Clifton
- Manjari Anant
- Jean Fan
ArticleOpen Access8 Dec 2023 Nature Communications
Generation of three-dimensional meat-like tissue from stable pig epiblast stem cells

Cultured meat technology promises to alleviate protein shortages, but still faces many challenges. Here, the authors achieve serum-free myogenic differentiation of porcine pre-gastrulation epiblast stem cells and generate meat-like tissue via edible plant-based scaffolds without any animal compounds.
- Gaoxiang Zhu
- Dengfeng Gao
- Jianyong Han
ArticleOpen Access9 Dec 2023 Nature Communications

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