The Scientific Observer Issue 28

The Environmental Impact of Biotech and Pharma Operations Immune Cartographers With Professor Emma Lundberg ISSUE 28 2 CONTENT FEATURE The Spatial Perspective With Professor Emma Lundberg Molly Campbell FROM THE NEWSROOM 04 ARTICLE The Environmental Impact of Biotech and Pharma Operations 06 Tanaaz Khan ARTICLE Should the BMI Measure Be Used in Medicine? 10 Molly Campbell ARTICLE Immune Cartographers: The Scientists Mapping the Immune Cell Atlas 13 Kate Harrison ARTICLE Experiences of LGBTQIA+ Individuals in Science 22 Kate Robinson, Mariana Gil and Kate Harrison 06 22 16 The Human Protein Atlas. An immunofluorescence image of the first part of the small intestine, called the duodenum. 3 EDITORS’ NOTE Dear Readers, Welcome to issue 28 of The Scientific Observer, the monthly magazine brought to you by Technology Networks. At the heart of every living organism lies a symphony of cellular processes, orchestrated with remarkable precision. Spatial biology, the science of understanding how biomolecules and cellular structures are arranged within living systems, helps us to unlock the secrets behind this intricate dance of life. In this issue, we are thrilled to feature an exclusive interview with the distinguished Professor Emma Lundberg, a trailblazer in this field. Her groundbreaking research has shed light on the spatial organization of biological processes, revealing exciting insights into disease mechanisms and potential therapeutic interventions. As we continue to push the boundaries of medical advancements, it is imperative to consider the environmental impact of our endeavors. Through in-depth analysis and expert perspectives, Tanaaz Khan seeks to understand how the pharmaceutical industry can strike a harmonious balance between scientific progress and environmental sustainability. In this issue, we’re also celebrating the invaluable contributions of the LGBTQ+ community in the scientific landscape. By amplifying the voices of LGBTQ+ scientists, we aim to foster an environment of inclusivity and acceptance, where diverse perspectives enrich our understanding of the world. We hope you enjoy this issue of The Scientific Observer. Subscribe to make sure you never miss an issue. The Technology Networks editorial team. Have an idea for a story? If you would like to contribute to The Scientific Observer, please feel free to email our friendly editorial team. CONTRIBUTORS Dr. Kate Harrison Kate Harrison, PhD, is a science writer at Technology Networks. Dr. Mariana Gil Mariana is a custom content manager at Technology Networks. Kate Robinson Kate is an assistant editor at Technology Networks. Dr. Sophie Prosolek Sophie is a senior science writer at Technology Networks. Molly Campbell Molly Campbell is a senior science writer at Technology Networks. Tanaaz Khan Tanaaz is a freelance writer specializing in long-form content for health and technology brands. 4 FROM THE NEWSROOM From the Newsroom David Clode / Unsplash. iStock. University of Oxford Professor Fritz Vollrath puts forth his “hot testicle hypothesis”. Vollrath suggests that elephants may carry more copies of p53 encoding genes due to an evolutionary mechanism that functions to protect sperm against harsh temperatures, but serendipitously offers cancer protection. JOURNAL: Trends in Ecology & Evolution. Hot Testicle Hypothesis May Explain Why Elephants Evolved Anti-Cancer Genes MOLLY CAMPBELL University of Queensland (UQ) researchers analyzed speed-daters to understand how we evaluate facial attractiveness. The study found that individuals rated faces similar to their own as more attractive. JOURNAL: Evolution and Human Behavior. We Are Attracted to People Who Look Like Us, Suggests Speed- Dating Study MOLLY CAMPBELL Conclusions from an upcoming report by the International Agency for Research on Cancer (IARC) were leaked. Reuters reported that the IARC was set to list the sweetener aspartame as a “possible carcinogen”. What does aspartame’s new designation mean, and should it alter your food choices? Aspartame’s New Status as a “Possible Carcinogen”: What Does It Mean? RUAIRI J MACKENZIE 5 FROM THE NEWSROOM 5 Karol Zub. Robina Weermeijer/Unsplash. Marcelo Leal/Unsplash Want to learn more? Check out the Technology Networks newsroom. In a highly unexpected defiance of evolutionary biology, feral populations of the American mink have been shown to reverse key changes to their brain size that occur during domestication. The study reaffirms the amazingly plastic nature of the animal brain, even in the face of many generations of selective breeding. JOURNAL: Royal Society Open Science. Feral Mink Brains Suggest That the Effects of Domestication Can Be Reversed RUAIRI J MACKENZIE The FDA has given the green light to Alzheimer’s disease drug lecanemab, converting it from accelerated to traditional approval. However, concerns regarding side effects, weighed against limited clinical benefits, raise concerns surrounding its use. Alzheimer’s Drug Gets Full FDA Approval Despite Safety Concerns SARAH WHELAN A new drug doubled the rate of remission in patients with ulcerative colitis (UC), an inflammatory bowel disease, in two Phase 3 clinical trials that investigated the efficacy and safety of mirikizumab in 1,281 patients with active, moderate-to-severe UC. JOURNAL: The New England Journal of Medicine Ulcerative Colitis Drug Doubles Remission Rates in Clinical Trial SARAH WHELAN 6 iStock From the production of medicines to the development of new treatments, the healthcare industry has always been at the forefront of cutting-edge science. Diseases that were untreatable a century ago are not even considered an issue now due to this industry’s intense research and development (R&D) efforts. However, even though the progress of the industry is nothing short of commendable, there’s a high cost associated with it – its environmental impact. A 2019 study by Health Care Without Harm found that the carbon footprint of the healthcare industry contributes to 4.4% of total global emissions. Another study found that the carbon footprint of public companies in this sector was at least 197 tonnes of carbon dioxide equivalent – or tCO2e – higher than the semiconductor, forestry and paper industry; for context, these three industries are considered some of the most carbon-intensive sectors. When you consider that the healthcare industry surpasses the rest, there’s a clear need to address the elephant in the room. My Green Lab, a non-profit sustainability organization, and Intercontinental Exchange Inc. (acquired by Urgentum), a provider of emissions data, recently collaborated to publish a report, The Carbon Impact of Biotech & Pharma: Progress to the UN Race to Zero. The report quantifies emissions from companies in the biotechnology and pharmaceutical industry and offers a realistic picture of the current state of healthcare sustainability. Let’s look at the report’s core findings and what it means for the future of this industry. 91% OF PUBLICLY TRADED COMPANIES DO NOT HAVE CLIMATE AGREEMENTS One of the most shocking findings of the study was that 91% of the publicly traded companies analyzed didn’t have concrete climate commitments in place, meaning they do not have an internal framework to meet the goal of a 1.5 °C world envisioned by the Intergovernmental Panel on Climate Change, or IPCC, by 2030. The Environmental Impact of Biotech and Pharma Operations TANAAZ KHAN 7 iStock The initial goal set by the IPCC to limit the effects of climate change was to ensure global temperature rise was limited to <2 °C above the average temperature levels we observed before the Industrial Revolution. Recently, IPCC’s report reduced that number to 1.5 °C – as we need to remove some of the carbon already present in the atmosphere to truly control the impact of climate change. However, with many carbon-intensive industries unable to control their emissions and governments not enforcing legally binding agreements, achieving a net zero carbon emission world by 2030 will be challenging. As per the Carbon Impact of Biotech & Pharma report, only 9% of the 75 analyzed companies have targets that align with the 1.5 °C target. The rest are either in the 2–3 °C or 3–5 °C warming range – far from the intended goal. François Le Scornet, a climate tech consultant, says that there are several reasons companies fail to address this issue, which go beyond ignorance and could be due to the lack of resources or understanding required to meet these goals. “Today, most companies understand that climate action will define many new policies and markets, and most CEOs now seriously address this topic. However, despite this realization and in the absence of direct external constraint (public policies or immediate customer pressure), some players may, unfortunately, choose to delay action and transparency around this topic,” he says. Even if the industry does take the measures required, it needs to be backed up by tangible progress. This is because the longer we wait, the harder it becomes to achieve the goal. For instance, in 2023, the industry needs to reach an annual carbon reduction rate of 9.28% as opposed to 7.03% last year. So, greenhushing and lack of efforts in this regard could cost not just the companies but the entire planet their future. The total carbon impact of public private companies rose to 260 million tCO2e from 2020 to 2021 As of 2021, the total carbon output of publicly listed companies in biopharma and biotech stands at 227 million tCO2e, and when we add in the total carbon output for private companies, it brings the total impact to 260 million tCO2e, according to The Carbon Impact of Biotech & Pharma: Progress to the UN Race to Zero report. These numbers have risen by 15% from 2020 – indicating a need to look closely at scope 1 and scope 2 emissions. Analysts recommend that companies address scope 1 and 2 as a priority, because they can have an immediate impact. However, ignoring scope 3 emissions could cause more harm than good in the long run, and the report’s findings indicate less interest in this sector, a conclusion that is supported by Science Based Targets. The organization provides a public list of companies that have signed up to the Science Based Targets Initiative (SBTi) to reduce their greenhouse emissions. The data is updated every single day – providing an up-to-date list of companies who are actively contributing to these efforts. As per the data published on 28th February 2023, most companies want to achieve a 20%–100% reduction in scope 1 and 2 emissions between 2025 and 2035. Alternatively, they only want to achieve a 10%–40% reduction in scope 3 emissions between 2025 and 2035. WHAT ARE SCOPE 1, 2 AND 3 EMISSIONS? Scope 1 emissions refer to emissions from a companies’ own/controlled sources. Scope 2 emissions, on the other hand, refer to the carbon impact from purchased energy, while scope 3 emissions are indirect, created within the company’s value chain (upstream or downstream). 8 Scornet says, “Companies need to perform an in-depth assessment of their scope 3 footprint in order to decide how to prioritize areas to focus on for reduction. Companies can use the Greenhouse Gas Protocol Guide or other recognized methodologies in their respective countries (e.g., “Bilan Carbone” in France) to do so. The idea is to address the most emissive activities by buying goods and services with lower carbon footprint, by avoiding unnecessary travel (by plane especially), by promoting a switch to lower emission fuels for upstream/downstream transportation and by manufacturing more energy efficient and durable products among other measures.” Another key finding from The Carbon Impact of Biotech & Pharma: Progress to the UN Race to Zero report was that scope 3 emissions were much higher than scope 1 and scope 2 emissions combined: approximately 4.3 times higher for publicly-listed companies, and 3.3 times higher for private companies. The report emphasizes that, while this ratio might seem alarmingly high, it is in fact lower than other industry sectors. The data indicates a need for companies in the life sciences sector to evaluate their value chain, as most scope 3 emissions arise from purchased goods and services and sold goods. The report also highlights a lack of standardized reporting for scope 3 emissions across the biotech and biopharma industries. While some companies have different methods of reporting their emissions data, others don’t even record it. Some of these reporting discrepancies may be attributed to the difficulty of obtaining such data from suppliers. For instance, if a company has over 1000 suppliers and, in turn, tens of thousands of stock-keeping units (SKUs), monitoring the carbon impact through the lifecycle of each SKU is incredibly challenging. As these emissions typically account for 65 to 95% of most companies’ carbon impact (across various industries), it’s crucial that they follow standardized protocols like those provided by Carbon Trust (Greenhouse Gas Protocol). LARGEST COMPANIES BY REVENUE ARE MAKING THE MOST PROGRESS IN UN RACE TO ZERO While the previous findings of the report are concerning, there is light at the end of the tunnel. Companies that have made the most revenue were also the ones that showed significant progress towards the UN Race to Zero initiative. Forty six percent of the largest companies based on revenue committed to the UN Race to Zero initiative at the time of the report’s publishing, as opposed to 31% in the previous year. These companies aim to cut carbon emissions by 50% by 2030 and reach net zero by 2050, indicating a step forward for the industry as a whole. Scornet emphasizes that this is an absolute must for this industry if it wants to survive the long-term challenges of being in business. “If pharmaceutical and biotech companies do not take the reduction of their carbon impact seriously, they shoot themselves in the foot in the long run. Delaying climate action probably appears as a short-term gain but it’s definitely a very significant strategic mistake in the long run,” he says. Scornet proposes the following reasons why companies in this sector should consider investing in climate change initiatives: • Indirect exposure to fluctuating oil and gas prices and exposure to more stringent regulation and taxation on carbon will remain an issue for the companies that don’t take action soon enough. • The new generation of talent – which is particularly sensitive to climate change – may be less attracted by companies that aren’t taking action. • It’s the moral responsibility of the pharmaceutical and biotech companies – which are already targeting healthier world as part of their mission – to address climate action. The pharmaceutical and biotech sector also crossed the Breakthrough Ambition threshold in 2021, defined as a timepoint where “sufficient momentum is generated among a critical mass of key actors, enabling them to break away from the business-as-usual path and together deliver breakthrough outcomes at pace”. This threshold was deemed as crossed when 20% of the major companies in the field joined the UN Race to Zero campaign. Moreover, in 2021, the My Green Lab certification program was selected as a key indicator of progress for the UNFCCC High-level Climate Champions’ 2030 Breakthroughs. It means that as long as 95% of laboratories in the MedTech and pharmaceutical sector receive this certification, it’ll be official that the industry is working towards the Breakthrough Outcome, i.e., they have the leverage to make a true difference by 2030. WHAT DOES THIS REPORT MEAN FOR THE FUTURE OF MEDICAL RESEARCH? While the biotechnology and pharmaceutical sector faces unique challenges in reducing emissions, it’s crucial to remember their potential to lead the way. Companies setting ambitious goals to reduce carbon pollution and investing in green energy should be celebrated as a success story – and hopefully will serve as an example for other industries. The prospects of net zero emissions by 2050 and abiding by the Paris Agreement certainly look achievable with cooperation from all sides – and every industry has a responsibility to help make this goal a reality. Scope 3 emissions were 4.3 times and 3.3 times higher for public and private companies, respectively when compared to scope 1 and 2 emissions We combine our scientific expertise with creativity to transform your ideas into standout pieces.WORK WITH USArticleseBooksPodcastsInfographicsOnline EventsVideosSEO Services 10 iStock The American Medical Association (AMA) – the largest association of physicians in the US – announced it has adopted a new policy aimed at clarifying how doctors use the body mass index (BMI) measure in medicine, suggesting it should be adopted in conjunction with other measures. Here, we explore where the BMI calculation came from, why it has a “problematic history” and the AMA’s policy. WHERE DID THE BMI CALCULATION COME FROM? In a quest to determine the characteristics of the “l’homme moyen” – the average man – Belgian mathematician Adolphe Quetelet devised the Quetelet index in the early 19th century. His analyses of human growth data in Belgian populations led him to conclude that, aside from childhood growth spurts and puberty, “weight increases as the square of the height”. Quetelet coined a formula whereby a person’s body size is calculated as their weight in kilograms divided by their height in meters, a measure that could then be compared across populations. In a time when calculators and electronic systems were non-existent, this simplistic calculation probably seemed a logical approach to stratify individuals, explore obesity levels and associated health outcomes. But well over a century later, Quetelet’s formula was relabeled the BMI by American physiologist Ancel Keys. In 1972, Keys and colleagues published an article in the Journal of Chronic Diseases promoting the metric as “preferable over other indices of relative weight”. Later endorsements from the National Institutes of Health and the World Health Organization (WHO) led to the BMI calculation finding firm roots in the medical community. Despite several updates regarding the thresholds for categorizing individuals as “healthy” or “obese”, the measure has persisted. Now, it is still used frequently as a tool to quantify health and disease risk, influence public health strategies and even to affect insurance reimbursements. Should the BMI Measure Be Used in Medicine? MOLLY CAMPBELL 11 The BMI calculation has faced much criticism over the years, with some researchers urging for its clinical applications to be dropped entirely. These calls for change appear to have reached a crescendo now that the largest association of physicians in the US has publicly cautioned its use. WHY IS BMI PROBLEMATIC? The AMA’s new policy was created based on the AMA Council on Science and Public Health’s report, which analyzed the pros and cons of the BMI measure – including its “problematic” history – and proposed new alternatives. BMI is considered a poor metric for measuring health based on a variety of factors. Firstly, it doesn’t distinguish fat from fat-free mass, which includes bone, muscle and other tissues. Individuals with the same BMI may therefore have very different bodily compositions. Take a lean athlete that carries a lot of muscle. Applying the BMI calculation, they might be deemed overweight. Beyond the adverse effects this classification could have on a physician’s ability to both accurately and fairly treat a patient, the psychological burden could be heavy. The potential glorification of a low BMI can also lead to unhealthy attitudes towards body image, food and self-acceptance in society and culture. BMI also does not account for how much of a person’s fat composition is made up of visceral fat – fat buried deep inside the body that wraps around the abdominal organs – which is associated with increased disease risk. Consequently, the AMA suggests the BMI should be used “in conjunction” with other validated approaches, including body adiposity index, measurements of visceral fat, body composition, relative fat mass, waist circumference and genetic/metabolic factors. The AMA also highlights an issue that has led many to consider the BMI metric as racist – it fails to acknowledge that healthy body shape and composition varies across different races and ethnic groups; Quetelet’s original index only considered white European bodies. “Our AMA recognizes the issues with using BMI as a measurement because: (a) of the eugenics behind the history of BMI, (b) of the use of BMI for racist exclusion and BMI cutoffs are based on the imagined ideal Caucasian and does not consider a person’s gender or ethnicity,” the Council on Science and Public Health report states. Beyond race and ethnicity, body shape and composition also vary depending on sex, gender and age-span. As a result, the association advises that it is “essential” to consider when applying BMI as a measure of adiposity that “BMI should not be used as a sole criterion to deny appropriate insurance reimbursement.” The report dedicates some time to analyzing the benefits of utilizing BMI – though the paragraph is petite compared to the list of disadvantages. The AMA says that BMI can be useful in monitoring the treatment of obesity: “Further, BMI is readily available, inexpensive, can be administered easily and is understood easily by patients. BMI can also be used as an initial screening tool to identify those at an elevated health risk because of excess body weight and poor distribution of fat mass,” the report reads. Though ultimately the association is clear in its statement that BMI loses its predictability when applied at the individual level. “There are numerous concerns with the way BMI has been used to measure body fat and diagnose obesity, yet some physicians find it to be a helpful measure in certain scenarios,” says AMA Immediate Past President Dr. Jack Resneck. “It is important for physicians to understand the benefits and limitations of using BMI in clinical settings to determine the best care for their patients.” MOLECULAR ALTERNATIVES TO BMI? BMI’s failure to consider the person as an individual certainly isn’t “on brand” for society’s move towards personalized medicine. Consequently, research groups are proposing alternative, molecular- based measures. Earlier this year, scientists from the Institute for Systems Biology (ISB) published their work outlining a “biological BMI” in Nature Medicine. Led by senior research scientist Dr. Noa Rappaport, the research team conducted multiomics profiling on blood samples from 1,000 individuals enrolled in the now closed Arivale wellness program. Using machine learning models, they generated molecular BMI scores, such as a metabolomics- or proteomics-based BMIs. “Biological BMI is a multi-dimensional molecular measure of BMI calculated from blood measurements of proteins, metabolites or clinical labs. It is a more comprehensive and accurate measure of metabolic health compared to the traditional BMI measure, which only considers height and weight,” Rappaport explains in conversation with Technology Networks. Unlike traditional BMI, biological BMI can identify misclassified individuals with a normal weight but disrupted metabolic health, who may not be currently monitored or treated.” HOW IS BMI CALCULATED, AND WHAT ARE THE CATEGORIES? BMI = kg/m2. The WHO created an expert consultation group in 1992, which was tasked with developing uniform categories of the BMI. The group published its categories in 1995, which included underweight (BMI in the range of 15 to 19.9), normal weight (BMI in the range of 20 to 24.9) overweight (BMI in the range of 25 to 29.9 and obese (BMI in the range of 30 or above). 12 Disseminate Your Research With UsWe know how important it is to disseminate your findings when working in research, but also what a challenge it can be to find opportunities beyond the conference hall. We want to address this!Technology Networks is spearheading a project to help researchers raise the profile of their work to a wider audience and increase coverage of the fantastic research papers out there that may not get the media attention they deserve.There is a lot of great research output and a very engaged audience that wants to hear about it, so share your work with us!Find Out More 13 iStock Since the discovery of antibodies and phagocytosis heralded the birth of immunology at the end of the 19th century, our understanding of the immune system has increased dramatically.1 However, there are still large gaps in our knowledge of how these cells function, and the role the immune system plays in a range of diseases. Characterization of the multitudes of different human immune cells by phenotype and spatial location is a key step towards fully elucidating immune function and dysfunction in infectious, autoimmune and inflammatory disorders. For the last several years, this complete mapping of the human immune system has been the goal of the Immune Cell Atlas. This atlas will be a part of the Human Cell Atlas (HCA), a worldwide scientific consortium founded in 2016, which aims to create a cellular reference mapping the position, functions and characteristics of every cell type in the human body. “The HCA is an open international collaborative consortium whose mission is to create comprehensive reference maps of all human cells as a basis for both understanding human health and diagnosing, monitoring and treating disease,” says Dr. Aviv Regev, founding co-chair of the Human Cell Atlas Organizing Committee and executive vice president and global head of Genentech Research and Early Development. Since its conception, the HCA, co-led by Dr. Regev and Dr. Sarah Teichmann from the Wellcome Sanger Institute, has grown to encompass more than 2,900 members in more than Immune Cartographers: The Scientists Mapping the Immune Cell Atlas KATE HARRISON 14 1,500 institutes across 94 countries. It is organized into 18 biological networks, including the Immune BioNetwork – the driving force behind the Immune Cell Atlas. CAPTURING THE DIVERSITY OF THE IMMUNE SYSTEM Even as just one Biological Network in the HCA, compiling the Immune Cell Atlas is an enormous task. There are over 30 trillion cells in the human body, and immune cells are almost ubiquitous throughout.2 In fact, the immune portion of the HCA was one of the first areas to be tackled. “Immune cells were some of the earliest cells to be studied with the single-cell techniques that we now rely on heavily, because immune cells in the blood were initially relatively more accessible for these techniques than tissue cells,” says Regev. Despite being readily available for sampling, characterizing immune cells can be challenging. Immune cells are extremely adaptive to their environment and will often express a range of different markers or phenotypes, depending on context. “One of the key principles of the Immune Cell Atlas is capturing the diversity of immune cells,” explains Dr. Alexandra-Chloé Villani, director of the single-cell genomics research program for the Center for Immunology and Inflammatory Diseases at Massachusetts General Hospital, a member of the HCA Organizing Committee and network co-ordinator for the HCA Immune BioNetwork, “There’s a lot of donor-to-donor variation, and variation across age, geographic regions and ethnic backgrounds. We also need to consider the plasticity of immune cells, and study them in different contexts, both in healthy donors and different disease states. We’re committed to mapping the whole spectrum of immune cells, across every demographic and perturbation condition.” Something else to consider for highly variable immune cells, is how to define a distinct cell type, compared to a temporary change in cell state. “Making sure we understand which cell types are there, and their full spectrum of potential states, is part of building a comprehensive atlas,” explains Regev. “These distinctions between types and states are not simple. Immune cells especially can be more malleable, or span a spectrum of states/types. Analyzing gene programs – sets of co-varying and often co-functional genes – can help us understand both.” In order to help decipher the phenotypes of different immune cells and their functions in various disease states, Regev’s research group pioneered computational methods in single-cell genomics. “In 2018, our lab contributed the first dataset to the Immune Cell Atlas, consisting of 1 million single-cell profiles of immune cells” Regev says.3 “Since then, we have continued to probe the identity and function of immune cells throughout the body, in different disease contexts including many kinds of cancer, inflammatory and immune diseases and COVID.”4,5,6,7 A WINDOW INTO HUMAN HEALTH Once complete, the Immune Cell Atlas will include immune cells from every aspect of the body, including primary and secondary lymphoid organs, and non-lymphoid tissues such as the skin and lungs. However, blood has so far been profiled most extensively by single-cell sequencing. “Blood, in some senses, is a window into human health,” Villani explains. “It’s easily sampled, and extremely useful in diagnostics. Blood studies are often focused on a single disease and individually small in scale, but in combination may have potential to produce new biological insights. As such, we need to start integrating data across studies to convert that into clinical utility.” Villani’s research group is currently working on integrating several data sets cumulating to 14 million blood cells gathered from both healthy donors and 27 distinct infectious and autoimmune disease states. “The goal here isn’t to create a detailed map of 27 distinct disease states,” clarifies Villani. “But to capture all possible immune cell identities by studying them across a range of different contexts and looking for common and distinct biological principles.” Once fully collated, these data will be an important resource for the Immune Cell Atlas and the wider field of immunology, to help elucidate the spectrum of health and disease. Villani and Regev’s earlier collaborative work using single-cell RNA sequencing (RNA-seq) to identify immune cells in blood samples helped fuel the formation of the HCA. The investigation identified a novel subset of dendritic cells (DCs) with T cell activating properties, and presented evidence supporting a taxonomy revision for wider DC subtypes.8 “We showed that it’s possible to predict the existence of a novel cell type through single-cell multiomics profiling, identify markers and then functionally characterize the cells to show they were truly distinct,” says Villani. This proof of principle study showed that new cell subsets could be identified through single-cell genomics analysis and further characterized using orthogonal approaches, which helped to build the foundational strategies now used across the HCA consortium. INCORPORATING NEW KNOWLEDGE INTO THE OLD For centuries, scientists have endeavored to catalog, classify and annotate cells of the human body, but only Characterization of the multitudes of different human immune cells by phenotype and spatial location is a key step towards fully elucidating immune function and dysfunction in infectious, autoimmune and inflammatory disorders. 15 recently has this been possible at such a specific, single-cell, molecular resolution and on such a huge scale. The development of highly accurate single-cell genomics techniques has enabled the simultaneous genome-wide quantification of mRNA in hundreds of thousands of cells. Integrating these methods with multiomics measurements (including transcriptomics, proteomics and epigenomics) helps to build a comprehensive picture of an individual cell’s properties, identity and relationships to other cells within the human body.9 However, using these novel methods isn’t without its challenges. “To really build a sophisticated view of a cell, you need to layer lots of different identities together, then try to sum them up and understand how they relate to the historical definition of the cells,” says Villani. “One of the challenges is that subsets of cells reported previously have been defined using limited sets of parameters, which makes it difficult to relate them to our new discoveries.” If the Immune Cell Atlas is to become a useful resource, accurately defining the identity of these cells using annotation terminology agreed upon within the immunology community is essential. To ensure this, the HCA consortium is developing a centralized platform for researchers to annotate cells, aggregating the molecular signatures used to define cells and the nomenclature used by individual researchers. This endeavor, known as the Cell Annotation Platform (CAP), is led by Dr. Villani and will be one of the key components of the HCA project. “The process of giving a cell type an identity is a cornerstone of biological research,” says Villani. “We’ve created an open-source centralized repository of persistent cell types and associated data sets. It allows a wide range of users to browse annotations of individual studies and give feedback on what we think is a unique cell type. We’re hoping it will bring classically trained immunologists together with experts in single-cell genomics to start deriving a common lexicon and consensus on cell identities.” The meta data collected in the CAP will also eventually empower machine learning approaches to provide automated cell annotation predicted for researchers to review for future datasets. MAPPING THE IMMUNE ENVIRONMENT OF TUMORS One important context for the immune system is malignancy and cancer. The immune system recognizes abnormal proteins on the surface of cancer cells, and targets them for destruction, therefore playing a key role in the control and clearance of tumors. In response, tumors engage in immunosuppressive and immune-evasive mechanisms. The tumor microenvironment often has a unique immune cell signature, which, if fully elucidated, could aid in the design of improved therapies or clinical outcome predictions. Several projects in the HCA focus on exploring the single-cell immune profiles of different cancers to reveal clinically relevant subpopulations.10,11,12 For example, one Immune Cell Atlas project examining the immune environment in clear cell renal carcinomas used singlecell RNA-seq and spatial techniques to discover a subpopulation of tumor-specific macrophages. Abundance of these macrophages were observed to increase in patients who suffered recurrence. Thus, the research identified these cells as both a potential prognostic biomarker and a potential target of therapy, and demonstrated the potential impacts of the HCA.13 The collaborative benefits of the HCA as a whole to subsequent research is already being seen, with Villani’s research as a prime example. One of her research projects examines immune- related adverse events (irAEs) to immune checkpoint inhibitor (ICI) treatment, a form of cancer immunotherapy. “We’ve been collecting clinical samples across organ systems affected by irAEs and are using single-cell multiomics strategies to analyze paired tissue and blood specimens to develop a detailed understanding of the molecular and cellular pathways involved in driving and sustaining irAEs ,” Villani explains. “And because we can work in the greater sphere of the HCA and the Immune Cell Atlas, we can get a better understanding of the biological context across organs through which these irAEs can develop.”14,15 The researchers were able to use data from another BioNetwork - the Heart Biological Network– as a reference, to help identify subpopulations of immune and non-immune cells involved in driving and sustaining ICI-myocarditis pathogenesis. INFORMING FUTURE THERAPIES Immune cells are found throughout the body and are now thought to play a role in almost all disease processes, whether communicable or not. Full characterization of the immune system and how it functions in different disease states would pave the way for new, more efficient treatments. Understanding how the immune system reacts in response to pathogens would allow the development of better targeted vaccines, for example. A comprehensive tumor immune atlas would enable the creation of safer, more efficient immunotherapies for cancer. Diagnostics could also be improved by the completion of the Immune Cell Atlas. “Right now, one of the most common diagnostic tests used in the clinic is the complete blood count (CBC), which tallies the numbers of certain kinds of blood and immune cells in a patient’s blood sample,” says Regev. “But these categories are actually very broad, so having a fuller picture of the kinds and states of immune cells in the blood and their roles would allow for the development of a much more specific diagnostic test - a “CBC 2.0.”” Ultimately, the Immune Cell Atlas will serve as a comprehensive, collaborative resource to benefit researchers all around the world in better understanding health and disease. However, it’s an ongoing endeavor with far more data needed before it can be considered complete. “It’s not a select club, it’s a grassroots initiative. Everybody is welcome to join us!” exclaims Villani. 16 iCStroecdkit Line 17 AUTHOR NAME FEATURE Image credit In spatial biology, scientists investigate the organization of cellular components in an effort to understand how their arrangement influences the cell’s function as a whole. The spatial distribution and organization of biomolecules such as DNA, RNA and proteins directs cellular responses. Dynamic alterations in this spatial organization – in response to internal or external stimuli – can subsequently change or disrupt these responses, potentially causing disease. Scientists have endeavored to peer into cells and disentangle their complex molecular makeup for hundreds of years. But only with the development of technologies such as advanced microscopy, high-throughput sequencing and computational image analysis could the spatial perspective be truly realized. Dr. Emma Lundberg, professor of bioengineering and pathology at Stanford University, professor in cell biology proteomics at the KTH Royal Institute of Technology and director of the Cell Atlas portion of the Human Protein Atlas, has been a key figure in such developments. As a postgraduate student at KTH, Lundberg first became interested in the rich data sets produced by bioimaging studies. Over the years that have followed, she has carved a career rich in scientific discovery, pioneering novel techniques for spatiotemporal analysis of proteins, receiving several prestigious awards along the way. It hasn’t always been an easy feat, however. As you’ll read, Lundberg has faced opposition at times, particularly when trialing novel experimental approaches and strategies to encourage public engagement in science. Thankfully undeterred, she continues to harness cutting-edge technologies – most recently artificial intelligence (AI) – to navigate the spatial realm. In an interview with Technology Networks, Lundberg discusses the evolution of spatial biology and her career, outlining how spatial insights can provide a deeper appreciation of the complex inner workings of cells. With Professor Emma Lundberg 18 Professor Emma Lundberg. Molly Campbell (MC): Can you talk to us about your career evolution – what led you to become interested in spatial biology? EMMA LUNDBERG (EL): I think a lot of what has happened in my career is serendipitous to some extent. I completed a Master of Engineering degree at the KTH Royal Institute of Technology, and during that time I was pretty set on pursuing a career in pharma – I’ve always been very interested in the human body. During my final thesis project, I worked within a research group that was generating small alternative scaffold binders that could be designed to bind to any potential protein, and I had so much fun. That was when I decided to do a PhD, which I hadn’t considered before, and was offered a position to continue the work from that final project. During my PhD, I spent time doing phage display, generating binders and learning deeply about proteins, which is probably where my interest in proteins – as the versatile and multifunctional molecules that they are – emerged. My PhD offered a solid foundation for what would become my research area of interest, as I did a lot of microscopy work. I was trying to generate binders that could also be used in imaging applications, and I am a visual person with a visual memory, so I enjoy working with images. In microscopy studies, you might have terrible results from an experiment, but that data can still look beautiful – it really appealed to me. I was also fascinated by the richness of the information that you can obtain through imaging studies, and how complex it can be to actually capture that information. During the final year of my PhD, I started working part-time as a group leader for the Human Protein Atlas (HPA). I had been considering moving abroad to complete a postdoctoral position, but I was offered the group leader position to set up and build the subcellular localization pipeline of the HPA. That’s how it started, and from then on, my focus has been on spatial proteomics. MC: How was that experience – working on the HPA in the early days? EL: It was super exciting. From a scientific perspective, it was a very unique project at that time, both in the world and in Sweden. It was almost a hybrid project that crossed industry and academia because it was so large scale, and our goals were long-term. For me, it was a very inspiring environment and a unique opportunity. It was difficult to complete a PhD and immediately become a group leader, but it was also a wonderful opportunity. MC: You recently joined the Stanford bioengineering department. What inspired this decision? EL: Stanford is a wonderful place, with a lot of inspiring and creative research going on. I had spent many years in the same department at KTH, where I also did my master’s and PhD, so it was time for a change, and I felt very inspired by the environment at Stanford. MC: How would you describe what spatial biology is? EL: Everyone knows that humans have specialized organs; we have a liver, we have a brain and we have a heart. These are entities that are specialized in a certain function. The same goes for cells. In cells, there are organelles and increasingly smaller systems with specialized functions. These systems are well partitioned in space – they are physically separated from each other. Through understanding how the cells and the proteins in the cells function, with the spatial context, we can better understand how cells function as a system. Another way to think about spatial biology is represented in our 2017 Science paper, where we show that half of all human proteins are in two or more compartments at the same time. This has often been neglected, as people tend to want to think that there is one gene, one protein and one function. That’s probably not the case most of the time, and in fact the protein could be in two different places performing two different functions. When we think about it from that perspective, you could explain spatial biology as though you are looking at a house or a village. There are different rooms, different compart- Professor Emma Lundberg 19 ments, and if a protein is in the “kitchen”, we might assume it is doing kitchen duties, whereas if it’s in the “laundry room”, it’s doing laundry – and if it’s in between, well perhaps it’s doing both. MC: In your opinion, what are some of the most interesting applications of spatial biology? EL: Of course, I would be inclined to say that the work our laboratory is doing is very interesting. We are trying to understand the spatial distribution of all human proteins with the goal of building a spatiotemporal model of all human cells. This work can help us to address the question of how the cell functions as a system. If we have that knowledge, can we build virtual cells? There are many, many interesting questions in spatial biology. A lot of diseases start with a protein being in the wrong place, or in the wrong place at the wrong time, which can have major functional consequences. I think, in general, connecting location to function is broadly applicable to many questions in biology that can lead to thousands of interesting applications. MC: Can you talk about key milestones for spatial biology that have occurred since the field emerged? EL: First let’s discuss the HPA, where there have been many milestones. Key examples are the ability to produce and validate antibodies at high capacity. Without that, we wouldn’t be where we are today. For the Subcellular Section of the Human Protein Atlas, which I am leading, a very important milestone occurred back in the day when we had just started the project and were unsure about what microscopes to use. This might sound trivial today, but it was a key decision to make in 2007. The pharmaceutical industry was using high-content screening microscopes, but they would just image everything with the exact same setting – we were moving one protein at a time, blindly, and there is so much variability in protein expression. I figured that this wouldn’t work for the project. I decided to take regular confocal microscopes and position them upright – essentially turning them the other way around to their regular configuration – and automate them ourselves. This was met with a lot of skepticism at the time. I was a new group leader and I was nervous as to whether this was the right decision or not. In the end, it was a great decision. We used the same microscopes for 15 years afterwards. Another milestone was being able to automate the imaging and the sample preparation steps so that we could prepare 500 samples a day and image them. We could do this research at a scale that had never been achieved before and with quality control measures in place. I think the next milestone would be the series of Science papers that we published from the HPA. There are different groups within the HPA, and we work in small teams in close connection with each other. It’s almost a “mini industry”, if you will. First, we published Tissue-based map of the human proteome in 2015, which was the first paper that outlined where proteins are expressed in human cells. Then we published A subcellular map of the human proteome in 2017. This was a series of milestones achieved in short succession, but keep in mind that we had been working on this research for over a decade. Since then, we have achieved several further milestones, particularly in relation to the way that we operate. We have transitioned from a brute force approach of “let’s just map everything” to addressing more targeted research questions. An example research study is our work published in Nature back in 2021, where we explored protein and RNA expression in relation to cell cycle progression. This required more advanced assays, we included single-cell transcriptomics and the work was more tailored. It was also conducted at high capacity. A more recent milestone that I believe will change a lot of aspects of spatial biology going forward is our ability to use machine learning to harness the information we obtain from the images. Instead of using our eyes to look at an image and say, “Oh how beautiful, this image is located in the mitochondria”, we can use AI to embed that information. We can turn an entire image into a vector of numbers that store information about that image and model the cell. Then we can start to integrate that data with other molecular measurements. For example, we built a structure of functional systems in a cell, demonstrating that we can model from the images. There is a lot of cool work going on too that we haven’t published yet. Generally, spatial omics might seem like a new field, but people have been looking through microscopes for a In microscopy studies, you might have terrible results from an experiment, but that data can still look beautiful – it really appealed to me. 20 long time – so it is actually quite old. We have been visualizing proteins and molecules for years, but our capacity to do this at a large scale has dramatically changed in the past two to three years. We are at an inflection point, particularly in spatial transcriptomics where technologies have really advanced. Now, we can visualize RNA in situ. You can look at hundreds and thousands of RNAs and explore gene expression patterns with high sensitivity and high resolution across cells and tissues. This ability has really changed the way that we can do biology; we can look at tumor heterogeneity, for example, and understand treatment responses based on differences in gene expression changes across regions of the tumor. Spatial proteomics is more technically complex because we can’t amplify proteins, so we’re a couple of years behind – but we’re getting there. There are many interesting technologies for multiplexed imaging that are established and emerging, and we’re seeing more people adopt them. So, we’re perhaps experiencing an inflection period as well. I’m very interested to see what happens with protein sequencing technologies and their impact on the field. MC: Much of science requires us to use our imagination to put information into context. It must be appealing in spatial biology to see your results in right there, in front of you. EL: Exactly. There is a microscopy conference called Seeing is Believing, and I think to some extent that is true – it is easier to believe something if you see it. However, it’s also important to not be fooled by the fact that you see something. It can be a double-edged sword. MC: You’ve spoken about the positive impacts that machine learning can have on spatial biology. Do you see any adverse effects at this stage? EL: Absolutely. We have a model that can generate synthetic microscope images that you really can’t tell apart from real images. You can see how such a model might have great usage as a foundation for whole-cell modeling, to predict where proteins that you haven’t stained are, for virtual microscope experiments, etc. But of course, you can also see the potential for misuse of such models. I think this issue extends beyond microscopy. I am currently working with a group in bioethics to think deeper about what the problems are and how we can address the issue of misuse. MC: Can you talk about some of the key challenges that you face, perhaps in your own field but also speaking broadly about the spatial biology field? EL: We can’t amplify proteins which is a huge challenge and one that is really hard to overcome. I think another core challenge when studying proteins compared to transcripts is the dynamic range of proteins. Some proteins are very abundant, and some proteins exist as a few copies that are regulated with high fidelity and are incredibly important for cell function. That is a difficulty we face with the technologies of today – maybe we still cannot detect low abundant proteins, or we only detect the high abundant proteins. In my everyday work, study design can be a challenge. Historically – and still today – we are working with antibodies to target proteins, which means we need to know what we want to target and study; we need to have a hypothesis. Compared to mass spectrometry, where you can obtain an unbiased total protein readout, this can be difficult. We want to be unbiased, but we still have to make a targeted selection. To circumvent that problem, we have been working with a technology that I am really excited about, which combines antibody-based methods and mass spectrometry, called Deep Visual Proteomics. We do highly multiplex imaging first to visualize all the cell types, then we use a laser microdissection microscope to cut out the different cell types before we do ultra-high mass spectrometry. The end result is the ability to project deep, unbiased measurements onto the original image. It’s not straightforward, but it’s super fun. What’s nice is that we’re using the imaging to guide the sample selection and then we get unbiased readouts. MC: You are clearly passionate about engaging the wider community with your work. Can you tell our readers about the citizen science project, “Project Discovery”? EL: We have generated millions of images in the HPA, and previously we annotated them all manually. This is fun but very time consuming. We reached a point where we realized that there is more information than what we can annotate in these images. We were thinking: How can we get the general public interested in this project to help us? I have a genuine belief that a lot of good things come from interactions between scientists and the general public – they are fun, but they are also inspiring. Spatial omics might seem like a new field, but people have been looking through microscopes for a long time. 21 The Human Protein Atlas. We were encouraged by previous projects that have asked the general public to support research efforts through playing a game. We teamed up with game developers at a company called MMOS and agreed that we would try to find an existing game and inject our images into that game. We ended up working with CCP Games in Iceland, so it was a three-part collaboration between CCP games, MMOS and us. For about a year we would meet every week and build the project, it was very fun – super different to other research projects! We built a “mini-game” called Project Discovery within an existing game called EVE online. While players are waiting for their friends in the game’s waiting room, they could play Project Discovery, and were made aware that they were contributing to science. I was also part of the game and had an avatar created called Professor Lundberg – she even has freckles. It was quite freaky! Initially, the scientific community was divided in their opinions about the game – some people thought it was cool and fun, others were questioning why we were doing it. We were nervous when we launched, but it was a great success. We reached our yearly goal within a week. It was obvious to us that this was a great approach to citizen science and to encourage the public to participate in scientific research. With projects like this, you can’t just develop it and leave it there – you have to engage with it, you have to answer questions in forums and participate, so it is a lot of work. My students were in the game while they were at the lab. The gamers did very well, and we could use the data to update the Protein Atlas. A lot of people reached out to us to let us know that they gained a passion for education and STEM because of the game, it was striking and really quite heartwarming. We hadn’t designed the game with that in mind, but it struck me that you can fulfill many purposes through an initiative like Project Discovery. MC: Were you happy with the avatar? EL: I was, but we had to change the outfit. MC: Are there plans for any similar projects right now? EL: Not at the moment, but it’s one of the reasons that I think it is really fun to be in Silicon Valley right now. It is a great place to be – I definitely have some ideas cooking. MC: What do you envision the future of your field will look like? EL: Short term, I think we are seeing a very rapid and focused development towards single-cell proteomics, which I believe will change the way we do proteomics and lead to a lot of insights. I think it will create a fundamental shift in the way that we work. When I talk about proteins, basically everything that we are doing is simplifying biology to consider one protein per gene, but we know that different proteoforms exist due to mechanisms such as post-translational modifications. We have a long way to go in terms of understanding how proteoforms modify cell function. This is a long-term challenge that I think novel technologies, such as protein sequencing and advanced mass spectrometry, can help with. I think we’re at the brink of a new era when it comes to structural cell modeling. If you think about the cell as having lots of building blocks, we know the genome project showed us the parts list, and then through these various atlas projects we have made an inventory of the parts list. What we don’t have is enough information on the assembly of the parts and how it leads to this functional cell machine. I hope that within 10 years we’ll have a model of the assembly of a cell. I envision a future where we can build virtual models of cells and use them to simulate how you would respond to a drug before being exposed to that drug. Even though we’re far from that point, I think we’re going to see how AI will propel this field forward in the coming years. Professor Emma Lundberg was speaking to Molly Campbell, Senior Science Writer for Technology Networks. An immunofluorescence image of cells derived from osteosarcoma. The DNA in the cell nucleus is shown in blue, and cytoskeletal elements called microtubules in red and actin filaments in green. 22 iStock An article published in Science Advances suggests that LGBTQIA+ persons are more likely than their non-LGBTQIA+ peers to experience social marginalization, harassment and limited career opportunities. In a survey conducted by the Institute of Physics, Royal Astronomical Society and the Royal Society of Chemistry, 49% of respondents agreed that there was an overall lack of awareness of LGBTQIA+ issues in the workplace. Each year since the Stonewall Riots in New York in 1969, June has served as Pride Month, a period dedicated to the celebration and commemoration of LGBTQIA+ people and culture. Here at Technology Networks, we are grateful for the opportunity to shine a light on the experiences of LGBTQIA+ individuals studying and working in science, technology, engineering, mathematics and medicine (STEMM), through our Pride in Science eBook. The following interviews are a selection of conversations from the eBook. Experiences of LGBTQIA+ Individuals in Science KATE ROBINSON, MARIANA GIL AND SOPHIE PROSOLEK 23 Dr. Claudia Wascher is associate professor at Anglia Ruskin University interested in the evolution of social behavior. She identifies as a lesbian, is married to a fellow academic and advocates removing barriers for dual career academic couples. After completing her PhD in 2009 at the University of Vienna, she spent several years as post-doc in international labs in Australia, Norway, Germany, France and Spain before starting a lectureship at Anglia Ruskin University in 2015. Wascher is passionate about improving equity, diversity and inclusion in science and leads the Faculty of Science and Engineering Athena SWAN self-assessment team at Anglia Ruskin University. She also coordinates several gender equality initiatives, for example, promotion support and continued professional training. In this interview, we spoke to Wascher to find out about her research and experiences as an LGBTQIA+ academic. Q: Can you tell us about your research interests? A: I am a behavioral biologist, interested in the evolution of social behavior. I specialize in group living birds and investigate physiological and cognitive mechanisms underlying social behavior. For my PhD, I recorded heart rate as a proxy of the physiological stress response in graylag geese. I studied how different social interactions affect heart rate. I found that heart rate in geese increased even if geese were only observing aggressive encounters, without being actively involved themselves. Further, heart rate increases more when geese were watching interactions with their partner or family members involved, compared to unrelated individuals. I am further interested in cognitive mechanisms mediating social interactions in corvids, mostly carrion crows. Carrion crows are highly social and frequently cooperate with other group members. In my research, I have shown that crows can differentiate between reliable and unreliable cooperation partners. My group currently investigates vocal communication in corvids. We are interested in the complexity of calls in different corvid species and how vocal complexity is driven by ecological and social factors. Q: What do you enjoy most about working in STEMM? What would you say are your proudest achievements? A: My proudest achievements definitely are the successes of my students and people I manage. It makes me extremely proud when my students successfully complete their studies, land great jobs, successfully publish or present their work. I am also very passionate about mentoring or managing colleagues and am very proud when they are successful (for example get promoted). I enjoy every aspect of working in STEMM. First, I really enjoy the great diversity of my job. No day is like any other and every day is filled with a wide variety of activities. In my everyday job I teach, conduct research, manage colleagues and research in my School. I am also leading gender equality work in my faculty, actively working remove barriers for underrepresented groups in science. I really enjoy the great flexibility in my job. My wife is also an academic, currently holding a position in Germany. Thanks to the great flexibility in academia, I am often able to work from Germany. Q: What are the main barriers for LGBTQIA+ people entering and progressing in STEMM, and what could be done to support them? A: I think that a lack of sense of belonging and navigating through a heteronormative environment are important issues. Generally, I found people in my field very accepting and supportive. However, at every workplace I felt the need to out myself very quickly to avoid people making wrong assumptions about my sexuality. The Claudia Wascher, PhD MARIANA GIL 24 iStock iStock lack of role models and visibility of LGBTQIA+ people can create a lack of sense of belonging and as a result LGBTQIA+ people are more likely to drop out of academia. I actively try to be a role model and visible for others in my field. In my field, biology, there are also real barriers when it comes to field work in countries which are less tolerant towards LGBTQIA+ people or where LGBTQIA+ identities are illegal. This absolutely needs to be considered when assessing the risk of field work. It is really important to educate the majority about potential risks for LGBTQIA+ people – which they are often not aware of. For example, the risk of being involuntarily outed. Q: Have you faced any obstacles in your career due to identifying as LGBTQIA+? A: I think I faced more obstacles by not conforming to stereotypical gender roles. I have been perceived as “too direct and outspoken”, overseen for jobs and promotions. Identifying as LGBTQIA+ I have also become very careful navigating the academic environment. I double check every communication and spend a lot of time thinking before I speak out, to make sure that my communications are perceived in the right way. On the one hand, this is an obstacle as I spend a lot of time reflecting on my conduct, but I also find– especially in the more senior positions I am in now – it also presents a strength being able to communicate very well with a diverse group of people. I also find that being LGBTQIA+ gives me a clear advantage managing people from diverse backgrounds because I understand the perspective of people in a minority position. Q: If you could give one piece of advice to young LGBTQIA+ researchers beginning their career, what would it be? A: I would definitely say “the field needs you, so be proud and confident pursuing a career in science”. As professionals, we are always shaped by our unique experiences and backgrounds. My field, for example, traditionally is very prone to categorize traits (e.g., behaviors) because this makes them easily quantifiable. However, recent advances in my field (e.g., personality research) suggest that biological traits often evolve across a spectrum and are only poorly represented in categories. As LGBTQIA+ person, I very much identify and agree with the idea that most biological traits occur on a spectrum rather than distinct categories. As such I do believe that my LGBTQIA+ identity makes me the best researcher I can be. Also, STEMM is a great field for LGBTQIA+ researchers. It is a very accepting, open-minded field, with a lot of great people from very diverse backgrounds who are keen to learn from and support each other. You will find great role models and supporters. Dr. Daniel Gillis identifies as a gay man and is an award-winning associate professor, statistician and interdisciplinary researcher in the School of Computer Science at the University of Guelph. Gillis is the co-founder of Farm To Fork, a project which used computer science to reduce hunger in Guelph. He is co-creator of ICON, a transdisciplinary undergraduate classroom that brings students from across campus together to work on social challenges, and he is co-founder of GuelphHacks and the Improve Life Challenge, a series of multidisciplinary annual hackathons held at the University of Guelph. He spends most of his time working on interdisciplinary teams which have focused on public health and ecological risk assessment, community- led software design, transdisciplinary pedagogy and bridging the digital divide. In this interview, we spoke to Gillis about his research, teaching and experience as an openly gay man working in STEMM. Daniel Gillis PhD SOPHIE PROSOLEK 25 Q: You work across multiple disciplines including statistics, pedagogy and computer science. Can you tell us about your research? A: It’s been a weird and winding path to get to where I am today, but now I’ve got four research programs and they’re all housed under the umbrella of “community- engaged research and teaching”. After I finished my PhD in statistics, I worked in ecological and public health risk assessment. I worked to develop new statistical methods, use statistical methods and new ways, or use new data to understand challenges related to public health, public health intervention, disease modeling and ecology. Some of my students have worked on things like DNA barcoding, mRNA and transfer RNA and how those data can be used to understand the viability of embryos or the successful breeding of livestock. When I transitioned into the School of Computer Science, I also had to train in computer science. I stumbled into the world of community-engaged software design and now work with community partners to develop software tools that support their missions. Most of our work is with not-for-profits and charitable organizations. We also work with indigenous populations. In fact, I’m heading to the Arctic again in just less than two weeks for a new potential collaboration with the Inuit in Cambridge Bay. I also have a research program that looks at transdisciplinary pedagogy and higher education. We look at improving the way we deliver course content and provide feedback to students. More importantly, we set students up in situations where they can work with communities from other disciplines to foster their foundational or transferable skills. Q: What do you love about STEMM? A: My love of STEMM started when I was very young; I was always fascinated by numbers, though I don’t know why. As a kid, I used to struggle to get to sleep because I was constantly doing math in my head and thinking about number patterns. I always loved the art of mathematics and the creativity that’s required. I also love the purity of it. As I went through my training, I was exposed to working with social scientists through the Public Health Agency of Canada. I got to see how a different kind of brain looks at the world; that reinvigorated my love of STEMM because I realized it can be way more than just the technical stuff. In terms of the work that I do, I love it when I can sit down and just do the maths – I find some sort of beauty in it, and I love the discovery. While there’s a lot of failures and a lot of “oh that didn’t work” there’s also “let’s try something new” and I love that element of it. Q: What would you say are your proudest academic achievements to date? A: So, one of the things that I love seeing in the classroom, or in lab work, is seeing the “light bulb moment” when students understand a concept. You're able to help them through the journey of discovery, and for me that’s one of the proudest moments. While I'm super proud of the awards that I've received, I think one of the greatest moments that I had was during teaching. It was the first time I had held a particular software design course; I ended up 50 minutes late to 1 hour and 20 minute long class – so there was only half an hour left. I was fully expecting to walk into an empty classroom, but every single student was there. There were four students at the front of the class, leading the discussion. They were all talking about the community project we were working on, and they were working on the things that they needed to. It was one of my proudest moments. It was excellent. Q: What do you feel are the main barriers for LGBTQIA+ people entering and progressing in STEMM? A: For me, the biggest barrier is the way the system is structured to begin with – it’s not been designed by or for people who don't fit the mold. If you’re different, you don't see yourself reflected in the people who are leading the universities or teaching in classrooms. From that point of view, I can definitely see how any equity-deserving community could feel that they don't necessarily belong. Based on some of the experiences I've had, I find that there’s just barrier after barrier thrown at you. There are comments that are made and microaggressions; I've had situations where people have asked me about my wife and kids, and these are people I've worked with for years! It’s not like I'm not “out” at work – they just fail to recognize that sometimes. While I don't think it's malicious, I think it's a lack of thinking. I also think that one of the things that push people away is that a lot of our efforts are hidden or unrewarded. We don’t want the next generation to have to deal with some of the stupid things that we've dealt with – and so we put ourselves in a situation to help them along. It's not recorded on our CVs and it's not rewarded by anybody. But it is extra work, and it can be triggering and exhausting. Q: If you could give one piece of advice to young LGBTQIA+ scientists beginning their career, what would it be? A: Do your best to not just survive, but to thrive and be proud of who you are. You don't have to be “out” or loud about your sexuality or gender, because unfortunately, so many folks in the community are in unsafe situations. But know that you're valuable, important and that your experiences and contributions are vital to the work that we do. If possible, find a community that supports you. If you don't have a local community, reach out to communities online. Just know that you're important and valued, despite what other people might say. It’s simple, just choose the groups and click the bubble. Our Facebook groups allow you to keep up to date with the latest news and research and share content with like-minded professionals. With three diverse groups there is something for everyone. Hi. How are you? Have you seen our Facebook groups? Thanks! I’ll come join the conversation. Come join the Neuroscience, News and Research Group here. Discover the Analytical Science Network Group here. Explore The Science Explorer Group here. No I haven’t. Could you tell me more? 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