Are you planning a wet-lab-based training course but don’t know where to start? There are so many things that could go wrong! After 6 years as a training lab manager at EMBL, I have seen it all. Here are some tips that could save you time, nerves and wasted lab consumables.
1. Identify your main contacts
Whilst the course organisers are the experts with regards to subject and course content, they are often very busy and trying to get hold of them can be a difficult task. Most of the time they will appoint an experienced colleague in their lab to help with the more practical and logistical aspects of organising the course. These people are the key players for my job – it is generally with them that I organise the practical set-up, because they know exactly what is needed, and when.
2. Timing is everything
Trainers are always surprised by how much longer people need in the lab for things they are doing for the first time. From my experience participants need twice as long in the lab as people who do the experiment regularly. So have this in mind when planning the schedule for a course. If possible, perform dry runs to get a better feeling of how long some experiments really take, and then double that time.
3. Back up, Back up, Back up
Not every experiment that we run during a course will be successful, but it is not the end of the world if you have prepared some back-up samples. The course days are already long enough – nobody wants to miss dinner to repeat a failed experiment, and troubleshooting is also a valuable lesson for the participants.
4. Everything clear?
Giving clear, coherent instructions is one of those things that sounds easy to do but in real life can actually be more complex, especially in a course setting. Some trainers don´t feel comfortable raising their voices to get everyone’s attention, meaning they have to repeat every single thing over and over again, which can cost valuable time.
5. Having good relationships to the main lab
You can plan a practical down to the smallest detail, but someone might still forget to tell you things like, “Oh, your incubator is actually too small to fit the instrument in there!” or “Oops! All my cells died over the weekend!”
In these situations it is key to have a good knowledge about who is doing what in the main lab and is willing and able to help out. Luckily my cheerful personality and baking skills have saved the one or other practical!
6. P p p poker face, p p poker face
As much as I love to have everything planned ahead of time, often this is not the reality when planning courses. Instructors often travel from abroad, and by the time they have arrived on-site, there are so many things that could go wrong. I refer to the first couple of days before the course starts as the “headless chicken mode”. But thanks to the experience and skill of our trainers, we always manage to overcome any difficulties that arise and are able to deliver our courses professionally – and the participants aren’t affected in the slightest!
7. Always be prepared for the unexpected
“It was working fine until this morning!”- This is one of the sentences nobody wants to hear during a course, but that is just how it is in the lab sometimes, and the training lab is no exception. You need to be a flexible thinker and be able to find a solution so the course can go on. Find a replacement instrument, shift the schedule around until the problem is solved. If there is no quick fix come up with another activity and cover the topic theoretically.
But to be honest in these cases I am so happy that I am doing this job at EMBL— because the EMBL people never let you down.
Identification and prioritization of candidate causal genomic variations from individuals affected by ASD
Authors: Giovanni Spirito (1), Diego Vozzi (2), Martina Servetti (3), Margherita Lerone (3), Maria Teresa Divizia (3), Giulia Rosti (3), Livia Pisciotta (4), Lino Nobili (4), Irene Serio (4), Stefano Gustincich (2), Remo Sanges (1)
Next generation sequencing (NGS) technologies enabled the extensive study of the genomics underlying human diseases. Namely whole exome sequencing (WES) represents a cost-efficient method which can lead to the detection of multiple classes of genomic variants and the discovery of novel disease-associated genes. One of the drawbacks of this approach however, is the large number of genomic variants detected in each analysis. Automated variant prioritization strategies are therefore required. This is particularly important in the case of complex disease such as ASD, whose genetic etiology is still poorly understood. To this aim we built a custom computational framework capable, from raw WES data, to automatically detect four classes of genomic variants (SNPs, indels, copy number variants and short tandem repeat variants) and prioritize them in regards to their relevance to a specific phenotype. We tested this framework on a selection of 29 trios including probands affected by severe and undiagnosed rare phenotypes and a small cohort of 10 trios all featuring healthy parents and one offspring affected by autism spectrum disorder (ASD). We were able to successfully detect rare and de novo high penetrance variants which have been validated and confirmed as causative among the undiagnosed probands. In the specific case of the ASD cohort we could highlight several genes which are not implicated in autism susceptibility, but nevertheless whose connections to genes relevant for ASD could suggest a possible involvement in the phenotype. Furthermore, our approach enabled us to detect several instances characterized by the presence of multiple candidate variants within genes belonging to the same canonical pathway in one proband. Our workflow allows to detect and prioritize multiple classes of genomic variants in order to both highlight rare high penetrance disease-causative mutation, and possibly reconstruct the genomics at the basis of complex ASD phenotypes.
(1) SISSA, Italy, (2) IIT, Italy, (3) Gaslini Institute, Italy, (4) University of Genova, Italy
Omics data integration for the identification of cell-type-specific gene regulatory networks and regulatory variants in Parkinson’s disease
Authors: Borja Gomez Ramos (1,2), Jochen Ohnmacht (1,2), Nikola de Lange (2), Aurélien Ginolhac (1), Aleksandar Rakovic (5), Christine Klein (5), Roland Krause (2) , Marcel H. Schulz (6), Thomas Sauter (1), Rejko Krüger (2,3,4) and Lasse Sinkkonen (1)
Genome-Wide Association Studies (GWAS) have identified many variants associated with different diseases. However, it is still a challenge to make sense of this data as the majority of genetic variants are located in non-coding regions, complicating the understanding of their functionality. In the last few years, it has been found that non-coding genetic variants concentrate in regulatory regions in the genome, which are cell type and cell-stage specific. In this project, we seek to identify functional Parkinson’s disease GWAS non-coding genetic variants that could make carriers more prone to developing PD. To do so, we are using induced pluripotent stem cell (iPSC) technology to differentiate somatic cells into midbrain dopaminergic (mDA) neurons, astrocytes and microglia. Assessing their chromatin accessibility, active chromatin regions and transcriptome, we can identify crucial regulatory regions in the genome, key transcription factors and derive the gene regulatory networks for the three different cell types. Then, we will map the non-coding genetic variants to the different regulatory regions and predict their effect in silico for the subsequent validation in vitro. This innovative approach will also identify novel factors controlling cell fate and cell identity.
(1) Life Sciences Research Unit, University of Luxembourg, Luxembourg, (2) Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, (3) Centre Hospitalier de Luxembourg (CHL), Luxembourg, (4) Luxembourg Institute of Health (LIH), Luxembourg, (5) Institute of Neurogenetics, University of Lübeck, Germany, (6) Institute for Cardiovascular Regeneration, Uniklinikum and Goethe University Frankfurt, Germany
In its first edition, the EMBO|EMBL Symposium: Metabolism Meets Epigenetics brought together 289 world-leading researchers who examined how metabolites and metabolic networks impact gene regulation, what their roles are in disease and how this opens novel therapeutic avenues.
In addition to the 21 invited speakers and 22 selected short talks, 142 posters were presented during the two poster sessions. Today we present three of the five award-winning posters decided by popular vote.
Citrate carrier links intermediate metabolism to histone acetylation upon ageing of mouse mesenchymal stem cells (MSCs)
Chromatin and metabolism interact in a reciprocal manner; on one hand metabolism-related genes are subjected to epigenetic modifications, which regulate gene expression. On the other hand, intracellular metabolism provides metabolites which can serve as essential co-factors and substrates for chromatin-modifying enzymes, affecting their activity. Although, it is well established that the process of ageing is accompanied by changes in metabolism and by chromatin alterations, their interplay in this context remains still poorly understood. In this study we sought to determine how ageing impinges on the relationship between cellular metabolism and the epigenome, using mouse mesenchymal stem cells from the bone marrow (BM-MSCs). In brief, our data suggest that there is a strong and direct link between the metabolic and the epigenetic states of the cell, with ageing-driven changes in metabolism regulating gene transcription and BM-MSC’s stemness, via alterations of the chromatin structure. We conclude that physiological ageing elicits changes in metabolism, resulting in suppressed glycolysis and impaired lipid biogenesis. Moreover, we demonstrate that during ageing there are lower levels of histone acetylation, despite the higher acetyl-CoA levels. We provide a solid explanation for this apparent discrepancy, pointing to the impaired export of acetyl-CoA from mitochondria to the cytosol. Indeed, the protein levels of the citrate carrier Slc25a1 decrease dramatically upon ageing. Using inhibition and supplementation experiments we provide a causal relationship between Slc25a1 function and the levels of histone acetylation, which directly influence chromatin accessibility and plasticity. Collectively, our data establish a tight, age-dependent connection between metabolism, epigenome and stemness and identify citrate carrier as the responsible protein for the mitochondrial-nuclear communication.
N-alpha-acetyltransferase 40 (NAA40) is distinct among other histone acetyltransferases (HATs) because it deposits an acetyl moiety on the alpha-amino group at the very N-terminal tip of histones H4 and H2A, instead on the lysine side chain. The biological function of this evolutionarily conserved enzyme remained unexplored for several decades because it was thought to mediate an inert modification. However, we previously showed that NAA40-mediated N-terminal acetylation of histone H4 (N-acH4) crosstalks with an adjacent arginine methylation mark to regulate yeast cellular aging in response to caloric restriction through transcriptional control of several metabolic genes. Therefore, we are currently interested in deciphering the function of human NAA40 in carcinogenesis. We recently showed that NAA40 is frequently upregulated in primary human colorectal cancer (CRC) samples. Remarkably, depletion of NAA40 and its accompanied reduction in N-acH4 blocked colon cancer cell proliferation and reduced cell survival in vitro and in xenograft models. We also found that loss of NAA40 expression or of its HAT activity markedly induce global histone methylation. Additionally, whole transcriptome analysis showed that NAA40 knockdown leads to upregulation of key enzymes involved in one-carbon metabolism. Intriguingly, silencing of methylenetetrahydrofolate reductase (MTHFR), which links the folate to methionine cycle, rescues the induction of global histone methylation and loss of cell viability triggered by NAA40 depletion. Hence, this recent work implies that NAA40 may transcriptionally regulate vital metabolic enzymes to control the flux of carbon units into the methionine cycle influencing S-adenosylmethionine (SAM) levels and triggering epigenome reprogramming of cancer cells. Overall, our findings thus far propose that NAA40 and its associated N-acH4 are crucial epigenetic modulators in tumourigenesis and implicate these factors in rewiring cancer cell metabolism.
Poster currently not available.
(1) University of Cyprus, Cyprus (2) Max Planck Institute for Biology of Ageing, Germany
Role of MOF acetyl transferase in mitochondrial homeostasis
Authors: Sukanya Guhathakurta (1), Christoph Martensson (2), Alexander Schendzielorz (3), Bettina Warsheid (3), Thomas Becker (2), Asifa Akhtar (1)
Mitochondria lies at the centre of cellular and organismal energy homeostasis, housing a large repertoire of enzymes that are required for the synergy of various metabolic pathways. Mitochondrial gene expression and protein acetylation are two important fundamental processes situated at the crossroad between mitochondrial function and metabolic status of a cell. Gene transcription in the mitochondria has been studied over several decades, but enzymatic acetylation of mitochondria proteins has stayed so far enigmatic. MOF acetyl transferase and its KANSL complex members dually localize to the nucleus and the mitochondria in mouse and human cells. The MOF-KANSL complex regulates metabolic gene transcription in the nucleus and expression of Electron Transport Chain (mtETC) components from the mtDNA, in a cell type dependent fashion. Regulation of nuclear gene transcription by MOF is well understood, however, its control of mitochondrial function remains elusive. Here, we report that loss of MOF leads to severe mitochondrial dysfunction in Mouse Embryonic Fibroblasts (MEFs), sprouting from a stalled oxidative phosphorylation. We address the mechanisms by which the enzyme maintains mitochondrial function in these cells by using a multi-omics approach. We discovered that the role of MOF-KANSL complex in the mitochondria of aerobically respiring cells could be decoupled from its regulation of steady state RNA levels, and could further be attributed to the acetylation of mitochondrial proteins. We characterize the role of acetylation on these proteins through generation of acetylated and non-acetylated mimics. Collectively our data, along with previously published works, suggests that MOF has emerged as a moderator to strike a harmony in the context of communication between the nucleus and the mitochondria. Recent progress on the project will be discussed.
(1) Max Planck Institute for Immunobiology and Epigenetics, Germany (2) Institute of Biochemistry and Molecular Biology, Germany (3) Institute for Biology II, Germany
In 2020 the EMBL Resource Development team and industry partners of the EMBL Corporate Partnership Programme will bring together academic and industrial scientists with interests in chemical biology, chemogenomic libraries, pharmacology, medicinal chemistry and bioinformatics for the EMBL Conference: Expanding the Druggable Proteome with Chemical Biology (5-7 February 2020).
We spoke to co-organiser Gerard Drewes from GSK Cellzome about how chemical biology is helping to expand the druggable proteome.
How would you define the “druggable proteome”?
This is the fraction of our >20,000 human proteins that can be functionally modulated by a drug. Drugs can be small molecules or large molecules such as therapeutic antibodies. Estimates of how many proteins are “tractable” vary widely, I think there may be around 5,000. Only a subset of these 5,000 would be “druggable” which means that modulating them with a drug will also have a therapeutic benefit.
How are advances in chemical biology helping to expand the druggable proteome?
Small molecules are still the main modality for intracellular targets. Deep pockets, typical for enzymes, are more easily tractable than shallow pockets typical for protein-protein interactions. Chemical biology has developed tools to explore different types of pockets. I am excited in particular by the potential of DNA-encoded libraries, and small fragment approaches with covalent modes of action. Some of these compounds will just be “binders” but these can be made into target degraders as PROTACs.
How can these advances help our understanding of disease biology?
If we had more chemical probes, we could use these in a standardised, controlled way to interrogate target function in cell-based models, organoids, and in some cases animal models. Yes, we have gene editing now, but that is not the same as pharmacological modulation.
We also need in vitro models that translate better to in vivo. Our old immortalised cell lines won’t do, we are going to need more work in primary cells, organoids, etc.
What are the main challenges facing scientists in this field?
Lack of standardised probe sets. Bad probe compounds, e.g. with bad selectivity, are still used and wrong conclusions drawn.
Lack of translational in vitro models.
Why is it important to bring industry and academia together to discuss this topic?
Academia brings creativity, agility, fast progress of new ideas and concepts, thinking out of the box.
Industry sometimes lacks these but knows how to develop a compound into a drug, which requires a host of technologies not readily available to academia. Also, industry requires a new generation of drug targets with better validation, and historically targets are often discovered in academia. Once a target hypothesis exists, academics and industry should ideally collaborate to figure out how to drug it.
What will be the main highlight of this conference?
Out of the posters presented, 4 were awarded a poster prize based on popular vote. Here we present the poster abstracts of four of the winners.
A computational modelling approach to characterizing postprandial glucose responses in individuals
Balazs Erdos (1), (2)*, Bart van Sloun (1), (2), Shauna O’Donovan (2), Michiel Adriaens (2), Natal van Riel (3), Ellen Blaak (4), Ilja Arts (2)
The large variability in the dynamic properties of the postprandial glucose response curves in individuals suggest that it is not sufficient to use average values or single time point measures of postprandial glycemia in order to characterize individuals’ glycemic control. Instead, approaches that are capable of capturing the dynamic events are necessary. In this study, we develop personalized computational models based on ordinary differential equations, to describe the glucose and insulin dynamics of individuals in response to an oral glucose tolerance test. We observed that these personalized models are capable of capturing a wide range of glucose and insulin dynamics including normal, prediabetic and type 2 diabetic responses as well as responses from intermediate states.
(1) TiFN, Wageningen, The Netherlands, (2) Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands, (3) Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, (4) Dept. of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
Predict nephrotoxicity associated with cisplatin-based chemotherapy in testicular cancer patients
In industrialized countries, testicular cancer (TC) is the most common solid tumor in men between 20 and 40 years old and besides being one of the most treatable types of cancer, the long-term side-effects of chemotherapy are worrisome, since they are largely irreversible. Their severity is normally related to the total amount of chemotherapy received, which makes that an important factor to a successful treatment. The standard treatment for TC is 3 cycles of cisplatin, etoposide and bleomycin (BEP), being that the number of cycles can vary between 4-5 or more if the prognosis of the patient is intermediate or poor. Some of the late side-effects include nephrotoxicity, which can be measured by the drop in glomerular filtration rate after the patient follows chemotherapy. Materials and Methods: Integrative machine learning models were built using a dataset of 400 Danish individuals in order to identify clinical and/or genomics features and classify patients at higher risk of developing nephrotoxicity given a treatment of BEP-cycles. Results: First, only clinical features, such as age at the time of treatment, dose of cisplatin, patient’s prognosis, and number of cycles, were considered, and relevant features were selected to use in the classifier (AUC 0.66, SD 0.02). The classifier was then optimized by adding genomics markers, which helped improving the prediction (AUC 0.75, SD 0.02). Conclusions: Therefore, it is proposed a machine learning algorithm which, by helping predicting nephrotoxicity in advance, can benefit to improve chemotherapy efficacy in TC patients. These data driven models can also be applicable to other cancers, such as ovarian, bladder, and lung cancer where more elderly patients are at risk of nephrotoxicity and identification upfront will have direct clinical implications.
Poster currently not available
(1) Technical University of Denmark, Denmark, (2) Copenhagen University Hospital, Denmark, (3) University of Chinese Academy of Sciences, China
Loss of N-glycanase 1 alters transcriptional and translational regulation
Petra Jakob (1), William Mueller (1), Sandra Clauder-Münster (1), Han Sun (2), Sonja Ghidelli-Disse (3), Diana Ordonez (1), Markus Boesche (3), Markus Bantscheff (3), Paul Collier (1), Bettina Haase (1), Vladimir Benes (1), Malte Paulsen (1), Peter Sehr (1), Joe Lewis (1), Gerard Drewes (3), Lars Steinmetz (1)
N-Glycanase 1 (NGLY1) deficiency is an ultra-rare, complex and devastating neuromuscular disease. Patients display multi-organ symptoms including developmental delays, movement disorders, seizures, constipation and lack of tear production. NGLY1 is a deglycosylating protein involved in the degradation of misfolded proteins retrotranslocated from the endoplasmic reticulum (ER). NGLY1-deficient cells have been reported to exhibit decreased deglycosylation activity and an increased sensitivity to proteasome inhibitors. We show that the loss of NGLY1 causes substantial changes in the RNA and protein landscape of K562 cells and results in downregulation of proteasomal subunits, consistent with its processing of the transcription factor NFE2L1. We employed the CMap database to predict compounds that can modulate NGLY1 activity. Utilizing our robust K562 screening system, we demonstrate that the compound NVP-BEZ235 (Dactosilib) promotes degradation of NGLY1-dependent substrates, concurrent with increased autophagic flux, suggesting that stimulating autophagy may assist in clearing aberrant substrates during NGLY1 deficiency.
(1) EMBL Heidelberg, Germany, (2) Stanford University, United States of America, (3) Cellzome, Germany
Data integration for prediction of weight loss in clinically controlled dietary trials
Rikke Linnemann Nielsen (1), Marianne Helenius (1), Sara Garcia (1), Henrik Munch Roager (2), Derya Aytan (3), Lea Benedicte Skov Hansen (1), Mads Vendelbo Lind (2), Josef Vogt (1), Marlene Danner Dalgaard (1), Martin I Bahl (3), Cecilia Bang Jensen (1), Rasa Muktupavela (1), Christina Warinner (4), Vincent Appel (5), Rikke Gøbel (5), Mette B Kristensen (2), Hanne Frøkjær (6), Morten H Sparholt (7), Anders F Christensen (7), Henrik Vestergaard (5), Torben Hansen (5), Karsten Kristiansen (6), Susanne Brix Pedersen (1), Thomas Nordahl Petersen (3), Lotte Lauritzen (2), Tine Rask Licht (3), Oluf Pedersen (5), Ramneek Gupta (1)
Diet is a key strategy in weight loss management. Advances in omics technologies research allow analyses of determinants of clinical interventions outcomes. We have previously reported diet-induced weight loss in non-diabetic middle-aged Danes in two clinically controlled dietary trials where the content of whole grain or gluten was changed. However, it remains elusive how predictable weight loss is at the individual level. We here classify weight loss responders and non-responders from the whole grain and gluten trials by integrating multi-omics data (host genetics, gut microbiome, urine metabolome) together with physiology and anthropometrics into random forest models. The most predictive models for weight loss included features of diet, gut microbial species and urine metabolites (ROC-AUC:0.84-0.88, model only with diet type ROC-AUC:0.62). Furthermore, we demonstrate that a model ensemble is robust to missing information of microbiome and metabolome profiles given features of physiology (including postprandial response), host genetics and transit-time (ROC-AUC:0.72).
Poster currently not available
(1) Technical University of Denmark, Denmark, (2) University of Copenhagen, National Food Institute, Technical University of Denmark, Denmark, (3) National Food Institute, Technical University of Denmark, Denmark, (4) Harvard University, United States of America, (5) The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark, (6) University of Copenhagen, Denmark, (7) Bispebjerg University Hospital, Denmark