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As the less familiar cousin of quantitative PCR moves mainstream, researchers have more options to choose from.

Knocking out a gene may be the most straightforward way to probe a protein’s function, but such experiments are blunt instruments. Removing a protein from a cell altogether can be both too much and too little, explains Kevan Shokat, a chemical biologist at the University of California, San Francisco. “You can either get no phenotype because another protein will replace it, or you’ll destroy a whole complex because it’s so central.” In response to this and other challenges, researchers have developed multiple systems in which proteins are engineered to respond to small molecules or light. Depending on the technology, scientists can inhibit proteins, activate them, bring them together or send them to specific cellular locations. Though less familiar than adding or removing genes, these techniques offer faster and more subtle ways to perturb protein function.

As more genomes are assembled from scratch, scientists are struggling to assess and improve their quality.

Such tools have been commercialized. Several vendors sell reprogramming systems using retroviruses and lentiviruses. A lentivirus produced by Stemgent and sold by Sigma-Aldrich encodes all four of the classic reprogramming factors (Oct4, Sox2, c-Myc and Klf4) in a single construct, with expression activated by doxycycline2. Millipore also offers polycistronic lentiviral reprogramming kits. Life Technologies sells a reprogramming kit that includes Sendai virus. And constructs for these and other tools are generally available from the nonprofit plasmid repository Addgene. Researchers working with mouse cells can use reprogramming systems that allow remarkable control over the transgenes. Separate teams led by Hochedlinger3 and by Rudolf Jaenisch4 at the Whitehead Institute in Cambridge, Massachusetts have crafted mice in which genes for pluripotency factors are placed under the control of doxycycline and inserted into a genomic locus that is never silenced by methylation and therefore is potentially active in any cell in the mice. These so-called reprogrammable mice allow iPS cells to be generated from any tissue: instead of adding viruses to introduce Scientists recognize the cells when they see them: compact colonies with clear edges, and large nuclei that spread almost to the cell membrane. Successful reprogramming experiments make i n d u c e d p l u r i p o t e n t s t e m (iPS) cel ls that resemble embryonic stem cells in both morphology and behavior. Yet appearance can deceive. “I’ve seen a lot of colonies that look beaut i fu l , but when you test them molecularly and functionally, the colonies are not real, not fully reprogrammed,” says Konrad Hochedlinger, a stem cell biologist at Massachusetts General Hospital. Ultimately, iPS cell lines are assessed with functional tests that require several weeks. For mouse iPS cells, that means generating mouse pups; for human iPS cells, testing for differentiation into all major lineages. These tests are time consuming and expensive, and so researchers need reliable ways to pick the best candidate colonies from a reprogramming experiment, much as an employer will sift through resumes before taking the time to interview job candidates. Surrogate markers of quality are important at several steps: picking which colonies to expand, picking which colony expansions to passage into cell lines, and figuring out which cell lines to submit to the most stringent tests. Picking colonies To make iPS cells, researchers introduce a suite of reprogramming factors into cells, usually by adding genes that encode transcription factors active in pluripotent cells. (A similar approach can be used to make differentiated cells directly; Box 1.) Cells respond to the reprogramming factors by dividing to form colonies, some of which can generate iPS cell lines. For reprogramming to go to completion, a cell must restart its own pluripotency genes and silence any introduced genes. Often ‘partially reprogrammed’ cells far outnumber fully reprogrammed ones. These partially reprogrammed cells can closely resemble embryonic stem cell colonies, but they cannot differentiate into the full range of cell types, and their gene expression may be quite different from that of embryonic stem cells. One way to reduce contamination by partially reprogrammed cells is to halt their growth early. For this, researchers sometimes use reprogramming factors that can be turned on and off at will. The introduced pluripotency genes can be constructed so that they are only expressed in the presence of a small molecule like doxycycline; removing doxycycline from the culture medium will silence them. Fully reprogrammed cells have already activated their own pluripotency genes and so continue to grow, but partially reprogrammed cells do not. Non-integrating systems, such as Sendai viruses and episomes, offer a similar advantage. Because they are not copied when cells divide, they are diluted out when cells expand, depriving partially reprogrammed cells of pluripotency factors. Growing cells under feeder-free conditions and with fully defined media can also cut down on the growth of partially reprogrammed cells1. Chimeric mice with all four reprogramming factors in the same genomic locus make producing iPS cells more straightforward. Re f. 3 Konrad Hochedlinger at Massachusetts General Hospital says that many beautiful colonies in reprogramming experiments fail to produce high-quality pluripotent stem cells.

‘Diseases in a dish’ are starting to show intriguing symptoms. Neurons made from the reprogrammed cells of individuals with schizophrenia form relatively few connections, but these increase upon exposure to a known antipsychotic1. Neurons made from individuals with Parkinson’s disease are more sensitive to oxidative stress2 and show mitochondrial deficits3. Those made from individuals with spinal muscular atrophy die quickly in culture4. Those from people with Alzheimer’s make higher concentrations of amyloid-b than those from people without the disease5 (Table 1). Not so long ago, these kinds of experiments would have been inconceivable. Compared with other organs, brain tissue is particularly hard to collect from patient biopsies. Neuroscientists have long had to make difficult choices between studying nonhuman cells or non-neural cells. But in 2007, researchers showed that human cells could be reprogrammed into a pluripotent state by adding genes active in the earliest stages of the embryo; the resultant cells could subsequently differentiate into all the major types of cells, including neurons. As reprogramming technology became more robust, academic hospitals around the world set up core facilities to generate cell lines from diagnosed patients. A cornucopia of induced pluripotent stem (iPS) cells has been derived from individuals diagnosed with myriad diseases. Thanks to reprogramming, onceprecious neural cells can now, in principle, be made in unlimited supplies. In addition, every cell line is genetically matched to someone with a known medical history. Human embryonic stem (hES) cells can also, in principle, supply endless quantities of cells. However, because making iPS cells is relatively easy and provides cells from a known individual for studying disease or developing therapies, much work on hES cells now involves using them as controls for comparison with iPS cells. The potential of iPS cells has generated a steady drumbeat of publications. But, like all exciting technologies, the road from proof of principle to routine practice is arduous. Researchers hoping to use reprogrammed cells to study brain disease first have to deal with a host of less glamorous tasks: reducing experimental variation across cell lines, pro

Efforts to improve stem cell culture are shifting to the surface. Efforts to improve stem cell culture are shifting to the surface.

Authors of the past five years' most highly cited research articles discuss their work and new directions in their respective areas.

Gene profiling using quantitative PCR is becoming higher throughput, but researchers must be careful in gathering their data.

The focus of metabolomic studies is shifting from cataloging chemical structures to finding biological stories.

Quantum dots, nanodiamonds and other nanomaterials broaden researchers' tools for watching biology.

Combinations of electrophysiology, two-photon microscopy and new tools for detecting neural activity show how neurons function in circuits.

MicroRNAs may be small, but these noncoding RNAs that regulate gene expression are creating a big stir. Finding differences in the expression of microRNAs between, say, healthy and diseased cells could potentially be used to diagnose diseases or to assess treatment effects. If researchers can understand how they work, microRNAs could provide tools for manipulating genes, not to mention help to untangle how genes are regulated. At first glance, studying microRNAs seems more manageable than studying the menagerie of other types of RNA. Typical expression profiling experiments for protein-coding genes examine thousands of molecules; those for microRNAs examine hundreds. But researchers are still figuring out the most reliable ways to measure these important molecules. The most common techniques for profiling microRNAs are deep sequencing, microarrays and quantitative real-time PCR (qPCR). All are supported by several commercial offerings (see Boxes 1–3). Though specific products and techniques vary, researchers generally agree on the relative strengths and weaknesses of the platforms. The best choice depends on the application, says Muneesh Tewari, who studies microRNAs at the Fred Hutchinson Cancer Research Center. “It’s a balance of cost, precision, accuracy and sample quantity,” he says. “If the purpose is to screen a bunch of samples to find a few microRNAs that change and you can tolerate a false negative, then the microarray may be the best platform. If the purpose is to detect microRNAs where the sample amount is limiting, then qPCR has better sensitivity, and if you are trying to see different isoforms or very similar microRNAs, then sequencing is going to be the best approach.” But not all researchers are aware of how the choice of product influences the data. “If you take the same sample and analyze microRNAs in different profiling technologies, the overlap can be surprisingly poor,” says Robert Blelloch, a stem cell biologist at the University of California, San Francisco. “It’s a really murky world,” he says. “The community has to come together to come up with a strategy here.”

To keep pace with accelerating sequencing machines, genomics researchers clean house and move toward the cloud.

With microfluidics and multiplexing, researchers can get more information from PCR products in less time and with fewer reagents.

As high-throughput techniques accelerate mapping of epigenetic marks, researchers are racing to find the biological meaning of these marks.

Mass spectrometry–based proteomics is still rapidly expanding, not just in terms of the methods and instruments but also the biological questions.

The current generation of antibodies has done more than make a few companies rich. It has laid the groundwork for ambitious companies to move to maturity.

The 'omics revolution offers plenty of decision-making tools. It's knowing how to use them that's key.

Nature Biotechnology's annual survey of public biotechnology companies finds some attrition, but on the whole a stronger sector.

Now that the generation of induced pluripotent stem cells is becoming routine, researchers can get on to the more exciting prospect of using the cells to make discoveries in disease and basic biology. Monya Baker reports.

Neurotechnology companies have promise, but lack funding and credibility. Monya Baker reports on this nascent area for startups.

Despite growing commercial interest in antimicrobial strategies that rely on antibodies, recent clinical trial failures suggest they are a work in progress.

Desperate patients are travelling abroad for dubious stem cell therapies. Monya Baker investigates the potential damage not only to human lives but to reputable stem cell research.

Genetically engineered bacteria made biotech drugs possible. Now, they are becoming drugs in their own right, Monya Baker reports.

Next-generation sequencing is uncovering more variants than ever before, but it also faces limitations.

O -Phosphoserine (Sep), the most abundant phosphoamino acid in the eukaryotic phosphoproteome, is not encoded in the genetic code, but synthesized posttranslationally. Here, we present an engineered system for specific cotranslational Sep incorporation (directed by UAG) into any desired position in a protein by an Escherichia coli strain that harbors a Sep-accepting transfer RNA (tRNASep), its cognate Sep–tRNA synthetase (SepRS), and an engineered EF-Tu (EF-Sep). Expanding the genetic code rested on reengineering EF-Tu to relax its quality-control function and permit Sep-tRNASep binding. To test our system, we synthesized the activated form of human mitogen-activated ERK activating kinase 1 (MEK1) with either one or two Sep residues cotranslationally inserted in their canonical positions (Sep218, Sep222). This system has general utility in protein engineering, molecular biology, and disease research.

It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.

Engineering precise genetic changes in a genome is powerful way to study gene function, and several recent papers describe new applications of gene-editing tools. Working with researchers at Sangamo BioSciences, Howard Hughes Medical Institute investigator Barbara Meyer and her colleagues at the University of California, Berkeley, described the first systems for making targeted genomic modifications in the roundworm Caenorhabditis elegans, a valuable model organism (Wood et al., 2011).

Researchers find new pieces in the puzzle of genome regulation.

Researchers use large libraries, focused libraries and rational design to engineer useful proteins.

Advances in microfluidics and imaging, combined with some high-profile studies, are increasing interest in whole-organism screening.

The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 1000 proteins, representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through www.dynameomics.org.

Nonlinear optical microscopy lets researchers see chemical composition in living cells and organisms.

Designing clinical trials that adapt midstream is billed as a cure for drug development blues, one that can save time, money and improve patients' lives. Are these new designs safe and effective or an expensive gimmick?