Table of contents


Special Feature

Method of the Year 2016

Epitranscriptome analysis is our choice for Method of the Year 2016. A News Feature looks at the history of the field, from the first discoveries of RNA modifications in the 1960s to recent transcriptome-wide methods. A Review describes the strengths and weaknesses of these methods, and a Commentary discusses the functional importance of a particular modification in stem cells. Our choice of eight methods to watch highlights areas we think will be influential in 2017 and beyond.





Quantitative predictions of protein interactions with long noncoding RNAs pp5 - 6

Davide Cirillo, Mario Blanco, Alexandros Armaos, Andreas Buness, Philip Avner, Mitchell Guttman, Andrea Cerase & Gian Gaetano Tartaglia



Research Highlights

Manipulating neurons in an activity-dependent manner p7

Neurons that are activated in response to a particular stimulus or behavior can be labeled or manipulated with a new method.

Colorful electron microscopy pp8 - 9

A multicolor approach specifically labels multiple targets in electron microscopy images.

Blend-and-shoot crystallography pp8 - 9

A rapid mix-and-inject serial femtosecond crystallography approach enables structure determination of ligand-binding intermediates.

Move over, Matrigel p10

A synthetic hydrogel matrix gives researchers greater control over intestinal organoid culture.

Thermal therapeutics p13

The development of temperature-inducible molecular bioswitches allows on-demand activation of synthetic genetic circuits in microbes.

Methods in Brief

Tools in Brief


News Feature

Special Feature: Method of the Year 2016

Epitranscriptomics: mixed messages pp15 - 17

Michael Eisenstein




Special Feature: Method of the Year 2016

Reversible RNA modifications in meiosis and pluripotency pp18 - 22

Arne Klungland, John Arne Dahl, Gareth Greggains, Peter Fedorcsak & Adam Filipczyk




Special Feature: Method of the Year 2016

Epitranscriptome sequencing technologies: decoding RNA modifications pp23 - 31

Xiaoyu Li, Xushen Xiong & Chengqi Yi


This Review describes the latest methods for profiling common epitranscriptomic marks, their scale, resolution and ability to quantify. It also discusses remaining challenges.


Methods to Watch

Special Feature: Method of the Year 2016

Global metabolomics p32

Allison Doerr


The ability to measure the metabolome on a global scale lags behind other omics techniques.

Special Feature: Method of the Year 2016

Expansion microscopy p32

Rita Strack


The changing face of super-resolution imaging

Special Feature: Method of the Year 2016

CRISPR targets RNA p33

Nicole Rusk


Having revolutionized DNA editing, CRISPR turns to RNA.

Special Feature: Method of the Year 2016

How single cells do it p33

Tal Nawy


Single-cell sequencing is poised to elucidate how cells contribute to tissue function.

Special Feature: Method of the Year 2016

Cryo-electron tomography p34

Allison Doerr


Cryo-electron tomography may facilitate in situ structural biology on a proteomic scale.

Special Feature: Method of the Year 2016

Faster brain imaging p34

Nina Vogt


Higher volumetric imaging rates shed light on the dynamics in neuronal networks.

Special Feature: Method of the Year 2016

Capturing microbial interactions p35

Tal Nawy


New approaches will expose microbial dependencies and environmental interactions.

Special Feature: Method of the Year 2016

Organoid culture p35

Natalie de Souza


Ex vivo organoid culture could revolutionize biology, but variability must be understood.


Technology Feature

Microbiology: the return of culture pp37 - 40

Vivien Marx


Sequencing technology drives microbiology and gives researchers new reasons to draw on classic techniques.


Brief Communications

Photometry unlocks 3D information from 2D localization microscopy data pp41 - 44

Christian Franke, Markus Sauer & Sebastian van de Linde


Three-dimensional localization microscopy can yield important biological insights. A photometric approach is described that allows users to gain 3D information from existing 2D images and to improve axial resolution obtained with existing biplane setups.

A statistical test for conserved RNA structure shows lack of evidence for structure in lncRNAs pp45 - 48

Elena Rivas, Jody Clements & Sean R Eddy


A new method, R-scape, tests whether observed sequence covariation supports a conserved secondary structure in RNA. The program finds no evidence for previously proposed conserved secondary structures in several lncRNAs.

Covalently circularized nanodiscs for studying membrane proteins and viral entry pp49 - 52

Mahmoud L Nasr, Diego Baptista, Mike Strauss, Zhen-Yu J Sun, Simina Grigoriu, Sonja Huser, Andreas Plückthun, Franz Hagn, Thomas Walz, James M Hogle & Gerhard Wagner


Membrane proteins can be stabilized in a native-like setting using lipid-bilayer-based nanodiscs encircled by a membrane scaffold protein. Covalently circularized nanodiscs now offer enhanced stability and control over nanodisc diameter size, improving the quality of structural data.

mScarlet: a bright monomeric red fluorescent protein for cellular imaging pp53 - 56

Daphne S Bindels, Lindsay Haarbosch, Laura van Weeren, Marten Postma, Katrin E Wiese, Marieke Mastop, Sylvain Aumonier, Guillaume Gotthard, Antoine Royant, Mark A Hink & Theodorus W J Gadella Jr


An extremely bright, truly monomeric RFP, mScarlet, is described that outperforms existing RFPs in diverse labeling applications, especially in FRET with ratiometric imaging.

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry pp57 - 60

Andrew Palmer, Prasad Phapale, Ilya Chernyavsky, Regis Lavigne, Dominik Fay, Artem Tarasov, Vitaly Kovalev, Jens Fuchser, Sergey Nikolenko, Charles Pineau, Michael Becker & Theodore Alexandrov


The authors present a computational framework for false-discovery-rate-controlled metabolite annotation from high-resolution imaging mass spectrometry data.

A scored human protein–protein interaction network to catalyze genomic interpretation pp61 - 64

Taibo Li, Rasmus Wernersson, Rasmus B Hansen, Heiko Horn, Johnathan Mercer, Greg Slodkowicz, Christopher T Workman, Olga Rigina, Kristoffer Rapacki, Hans H Stærfeldt, Søren Brunak, Thomas S Jensen & Kasper Lage


InWeb_InBioMap (InWeb_IM for short) is a scored, integrated human protein–protein interaction network resource aggregated from public, experimentally determined protein–protein interactions. The resource enables functional interpretation of large-scale genomics data.

novoBreak: local assembly for breakpoint detection in cancer genomes pp65 - 67

Zechen Chong, Jue Ruan, Min Gao, Wanding Zhou, Tenghui Chen, Xian Fan, Li Ding, Anna Y Lee, Paul Boutros, Junjie Chen & Ken Chen


The novoBreak software provides sensitive, accurate, and comprehensive detection of structural variation in somatic next-generation sequencing data.

TACO produces robust multisample transcriptome assemblies from RNA-seq pp68 - 70

Yashar S Niknafs, Balaji Pandian, Hariharan K Iyer, Arul M Chinnaiyan & Matthew K Iyer


TACO generates a consensus transcriptome with improved accuracy from multisample RNA-seq data.

CHARMM36m: an improved force field for folded and intrinsically disordered proteins pp71 - 73

Jing Huang, Sarah Rauscher, Grzegorz Nawrocki, Ting Ran, Michael Feig, Bert L de Groot, Helmut Grubmüller & Alexander D MacKerell Jr


An all-atom protein force field, CHARMM36m, offers improved accuracy for simulating intrinsically disordered peptides and proteins.



DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo pp75 - 82

Meghan Zubradt, Paromita Gupta, Sitara Persad, Alan M Lambowitz, Jonathan S Weissman & Silvi Rouskin


DMS-MaPseq enables genome-wide and target-specific RNA secondary structure probing of even rare or heterogeneously structured RNAs in vivo and was used to study structure involved in translation regulation as well as nascent transcripts.

Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments pp83 - 89

Alina Selega, Christel Sirocchi, Ira Iosub, Sander Granneman & Guido Sanguinetti


BUM-HMM is a statistically robust modeling pipeline for interpreting high-throughput RNA structure probing data, including that from transcriptome-wide experiments.

Atmospheric pressure MALDI mass spectrometry imaging of tissues and cells at 1.4-μm lateral resolution pp90 - 96

Mario Kompauer, Sven Heiles & Bernhard Spengler


An instrumental setup for atmospheric pressure MALDI-based mass spectrometry imaging with improved lateral resolution enables subcellular-level details to be resolved.



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