Sexual reproduction may have never become possible if organisms hadn’t evolved a way to restrain the immune system during fertilization, according to a new study from the lab of Sagi Shapira, PhD, assistant professor of systems biology.

The study, published today in Immunity, took an in-depth look at how vertebrate eggs are fertilized.

To fight invading pathogens, all organisms (including vertebrate cells) are programmed to detect and attack any DNA and foreign RNA found outside of the nucleus in the cell’s cytoplasm. It’s usually a safe bet that any DNA found in the cytoplasm is from a foreign microbe, because the cell’s own DNA is safely sequestered in the nucleus. But during fertilization, DNA and RNA from sperm may be briefly exposed to the cytoplasm of an egg—and to the danger of being recognized and attacked.

For fertilization to succeed, Dr. Shapira reasoned that something must prevent the immune system from attacking DNA during fertilization and searched for candidates in the genome.

The search revealed a gene called NLRP14, which encodes a protein that Dr. Shapira’s laboratory demonstrated to play a role in the innate immune system. Without NLRP14, the immune system induces a strong inflammatory response to DNA and RNA found in the cytoplasm, and the fertilization process comes to a halt.

Andrew Anzalone and Sakellarios ZairisMD/PhD students Andrew Anzalone and Sakellarios Zairis combined approaches based in chemical biology, synthetic biology, and computational biology to develop a new method for protein engineering.

The ribosome is a reliable machine in the cell, precisely translating the nucleotide code carried by messenger RNAs (mRNAs) into the polypeptide chains that form proteins. But although the ribosome typically reads this code with uncanny accuracy, translation has some unusual quirks. One is a phenomenon called -1 programmed ribosomal frameshifting (-1 PRF), in which the ribosome begins reading an mRNA one nucleotide before it should. This hiccup bumps translation “out of frame,” creating a different sequence of three-nucleotide-long codons. In essence, -1 PRF thus gives a single gene the unexpected ability to code for two completely different proteins.

Recently Andrew Anzalone, an MD/PhD student in the laboratory of Virginia Cornish, set out to explore whether he could take advantage of -1 PRF to engineer cells capable of producing alternate proteins. Together with Sakellarios Zairis, another MD/PhD student in the Columbia University Department of Systems Biology, the two developed a pipeline for identifying RNA motifs capable of producing this effect, as well as a method for rationally designing -1 PRF “switches.” These switches, made up of carefully tuned strands of RNA bound to ligand-sensing aptamers, can react to the presence of a specific small molecule and reliably modulate the ratio in the production of two distinct proteins from a single mRNA. The technology, they anticipate, could offer a variety of exciting new applications for synthetic biology. A paper describing their approach and findings has been published in Nature Methods.

Saeed TavazoieSaeed Tavazoie, a professor in the Columbia University Department of Systems Biology, has been named a recipient of a 2015 National Institutes of Health Transformative Research Award. The grant will support research to develop state-of-the-art experimental and computational methods for comprehensively mapping and modeling all pairwise molecular interactions inside cells. 

The Transformative Research Award is a part of the NIH Common Fund’s High-Risk, High-Reward Research program, which provides critical funding to scientists it recognizes as being exceptionally creative and who propose particularly innovative approaches to solving key problems in biomedical research. The Transformative Research Award is designed to support projects that use methods and perspectives that are unconventional and untested, but show great potential to create or overturn fundamental paradigms.

Alex Lachmann
Alex Lachmann during his presentation to the RNA-Seq "boot camp."

In June 2015, the Columbia University Department of Systems Biology held a five-part lecture series focusing on advanced applications of RNA-Seq in biological research. The talks covered topics such as the use of RNA-Seq for studying heterogeneity among single cells, RNA-Seq experimental design, statistical approaches for analyzing RNA-Seq data, and the utilization of RNA-Seq for the prediction of molecular interaction networks. The speakers and organizers have compiled a list of lecture notes and study materials for those wishing to learn more. Click on the links below for more information.

Tuuli LappalainenTuuli Lappalainen has joined Columbia University as an assistant professor in the Department of Systems Biology. Dr. Lappalainen is a specialist in the analysis of RNA sequencing data, with research interests including functional variation in the human genome, population genetic background of variation in the human genome, and interpretation of genome function.

Dr. Lappalainen joins the Department of Systems Biology in co-appointment with the New York Genome Center (NYGC), where she will also serve as a Junior Investigator and Core Member. Based in lower Manhattan, NYGC is a consortium made up primarily of New York-area institutions that is designed to translate promising genomics-based research into new strategies for treating, preventing, and managing disease. This co-appointment with Columbia University — an institutional founding member of the NYGC — will enhance collaboration between the two institutions. (Read an interview with Dr. Lappalainen at the New York Genome Center website.)

An extensive microRNA-mediated network of RNA-RNA interactions

Genome-wide inference of sponge modulators identified a miR-program mediated post-transcriptional regulatory (mPR) network including ~248,000 interactions.

For decades, scientists have thought that the primary role of messenger RNA (mRNA) is to shuttle information from the DNA to the ribosomes, the sites of protein synthesis. However, new studies now suggest that the mRNA of one gene can control, and be controlled by, the mRNA of other genes via a large pool of microRNA molecules, with dozens to hundreds of genes working together in complex self-regulating sub-networks.