The Scientific Observer Issue 28
Magazine
Published: August 11, 2023
|
Last Updated: February 29, 2024
Issue 28 of The Scientific Observer features an exclusive interview with Professor Emma Lundberg on the importance of understanding the spatial organization of biological processes. We also confront the environmental impact of biopharmaceutical research and explore why diverse perspectives in science enrich our understanding of the world.
Issue 28 highlights:
- Should the BMI Measure Be Used in Medicine?
- The Spatial Perspective With Professor Emma Lundberg
- Experiences of LGBTQIA+ Individuals in Science
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
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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).
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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
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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.
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ISSUE 04, JULY 2021
Privacy in
Brain:
of
Neurotechnology
ISSUE 06, SEPTEMBER 2021
Molecules,
Mountains and
Making the World
a Better Place
Regulating Heavy
Metals in Baby Food
#PostItNotePhD
The Alpha and Omega
of COVID-19: Yes,
the Pandemic Will
End (but Not Soon)
ISSUE 08, NOVEMBER 2021
Sustainable
Science
and the
Road to
Net Zero
Uncovering Key
Interactions
Between Cancer-
Driving Proteins
Addressing
Disparities in
Healthcare and
Clinical Research
Closing the
Vaccine Gap
ISSUE 03, JUNE 2021
as a
Long-Hauler
ISSUE 01, APRIL 2021
The Physicality
of Consciousness
ISSUE 07, OCTOBER 2021
Return From
Extinction
The Neuroscience
of Creativity
Hidden Secrets of the
Human Microbiome
COVID-19: Vaccine
Stockpiling
ISSUE 10, JANUARY 2022
What the World’s
First Pig to Human
Heart Transplant
Could Mean for the
Future of Transplants
Unpicking the
Complexities of the
Cancer Microbiome
A New Approach to
Treating Superbugs
Influenza and
the Holy Grail
Vaccine
ISSUE 09, DECEMBER 2021
Lost Women
of Science
Why the Meat
Paradox Causes
Cognitive Dissonance
for Millions of People
The Omicron Variant
Highlights the Need
for Smarter, Future-
Proof Vaccine Design
The Pursuit
of Global,
Sustainable and
Cooperative
Open Science
ISSUE 02, MAY 2021
Biodegradation of
Synthetic Plastic in
the Marine Habitat
A Step Closer to
Orally-Delivered
Insulin for Diabetes
Three Psychology
History, Mystery
and DNA Analysis
ISSUE 05, AUGUST 2021
Mental Health and
Mental Illness in
Higher Education
Tapping the Ancient
Power of Microalgae
Turning On the
Vaccine Tap
All
Cancers,
Great and
Small
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