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Reyes, M.

Publications and source records attributed to Reyes, M..

At least 19 recordsLinked to original sources
bioRxiv2026

Oligonucleotide genetics for Pseudomonas aeruginosa enables high throughput hypomorph screening

The continual advancement of genetic tools has been critical to our modern understanding of bacteria, with transposons, plasmids, and homologous recombination becoming workhorses of molecular microbiology. However, precisely specified reverse genetic approaches remain painstakingly slow and inaccessible, particularly in non-model strains. This reality is exemplified by the opportunistic pathogen, Pseudomonas aeruginosa (Pa), where conventional allelic exchange remains the dominant reverse genetic method. Here, we adapt a rapid genetic toolkit for use in Pa, relying directly on commercially available oligonucleotides (120 bases) to create precise genomic mutations through homologous recombination (i.e. oligo recombineering). Oligo Recombineering followed by Bxb-1 Integrase Targeting (ORBIT) uses a short attachment site for an integrating plasmid, which provides traditional antibiotic selection and can also carry flexible cargo. We establish Pa ORBIT works effectively for gene deletion without off target mutations, optimize protocol parameters (e.g. oligo length, electroporation), and demonstrate markerless and clean deletions. Importantly, our toolkit works well in clinical Pa strains as demonstrated by constructing efflux pump deletions in three different isolates. To test the high throughput capabilities of Pa ORBIT, we created over 160 degron-based hypomorphs (i.e. knockdowns) across 43 essential proteins in a pooled mutant library. Upon screening this library with and without antibiotics, we identify highly vulnerable essential proteins and hypomorphs that display synergy with clinical drugs. Therefore, ORBIT can be used for cutting edge low and high throughput investigations in this priority pathogen, setting the stage for answering critical basic and clinical science questions. SignificanceTo understand bacterial genomes, researchers need access to rapid, flexible, precise and high throughput genetic perturbation tools. Here we present an oligonucleotide-based method that satisfies these requirements for use in the opportunistic pathogen, Pseudomonas aeruginosa. By relying on oligos to encode genomic homology arms, no molecular cloning is required - making these tools rapid, robust, and scalable. We benchmark gene deletions in both lab and clinical strains, opening the possibility of rapid genetic studies across the P. aeruginosa pangenomic space. At high throughput, we use an oligo pool to create a mutant library of degron tagged essential proteins. These knockdowns (i.e. hypomorphs) show certain essential genes are highly vulnerable and others are synergistic with clinical drugs, providing insight into future antibiotic and co-therapy development.

microbiology↗
bioRxiv2026

A decrease in specific health-associated commensals is linked to progressive periodontal tissue destruction independent of dysbiotic community profiles

Periodontitis is a chronic inflammatory disease associated with dysbiotic microbial communities that leads to destruction of the tooth-supporting tissues. The transition from host-microbial periodontal homeostasis to disease remains poorly understood. The murine ligature-induced periodontitis model was employed to characterize the temporal dynamics of the subgingival microbiome and host tissue features. Ligatures were placed in C57BL/6N mice, and collected on days 0, 1, 3, 5, and 7 post-induction. Bacterial load, alveolar bone loss, immune cells (CD45), cells with osteoclastogenic potential (TRAP) and collagen destruction were analyzed. Additionally, the V4 region of the 16S rRNA gene was sequenced for ecological analyses, including co-occurrence networks and functional prediction. Spatial distribution of the most abundant species was visualized using CLASI-FISH microscopy. Finally, association models were performed to link bacterial abundances with time and tissue parameters. The most substantial microbial shift occurred on day 1, and a dysbiotic community was established by day 3. CD45 cell infiltration increased as early as day 1, preceding the rise in TRAP cells on day 3 and the onset of tissue destruction on day 5. By day 7, predicted bacterial functions included protein export, lipid and galactose metabolism. Health-associated taxa were identified, and their abundance correlated positively with collagen integrity and negatively with immune cell infiltration and bacterial load, highlighting their role in homeostasis. These findings provide a high-resolution temporal map of microbiome-host interactions during experimental periodontitis establishment and identify specific microbial and cellular windows for potential therapeutic intervention.

microbiology↗
bioRxiv2025

Zooplankton feeding behaviour and survival to toxic and non-toxic cyanobacteria during the seasonal bloom progression of a eutrophic lake

Harmful cyanobacterial blooms pose increasing threats to aquatic ecosystems and human health; yet, the role of zooplankton grazing in regulating blooms remains understudied. We investigated the seasonal feeding behaviour and fitness consequences of feeding preferences in natural zooplankton communities for toxic (microcystin-producing) versus non-toxic cyanobacteria across temperature gradients in eutrophic Lake Greifen, Switzerland. We conducted monthly experiments from April to October 2023 to test the grazing behaviour of four zooplankton groups (daphnids, calanoid copepods, cyclopoid copepods, and microzooplankton) exposed to mixed diets of green algae and either toxic or non-toxic Microcystis strains at 15{degrees}C and 25{degrees}C. Contrary to expectations of cyanobacteria avoidance, zooplankton exhibited predominantly non-selective grazing throughout the seasonal succession, consuming both toxic and non-toxic cyanobacteria at similar rates, regardless of temperature. Notably, during the peaks of phytoplankton abundance (April and September), mesozooplankton demonstrated a selective preference for cyanobacteria over green algae, particularly non-toxic strains. Temperature effects were subtle but revealed metabolic constraints: elevated temperatures occasionally triggered selective consumption of cyanobacteria in copepods, while fitness costs (survival) from exposure to toxic species were mostly restricted to transitional bloom periods and high-temperature conditions. These findings suggest that toxic cyanobacteria may not always evade grazing pressure through secondary metabolite deterrent effects. Our results suggest that zooplankton communities can adapt and graze on cyanobacteria regardless of toxicity under the tested conditions, even during bloom conditions. These observations highlight the potential for zooplankton to interact with cyanobacterial populations, which may have implications for bloom prediction and management strategies, particularly under climate warming scenarios. Manuscript HighlightsO_LIZooplankton grazed on toxic and non-toxic cyanobacteria with similar effects across seasons in a eutrophic lake characterised by toxic blooms. C_LIO_LINatural zooplankton communities showed no systematic avoidance of microcystin-producing cyanobacteria. C_LIO_LIHigh temperature effects on feeding selectivity were subtle and taxon-specific. C_LIO_LIFitness costs from exposure to cyanobacteria (including microcystin-producing isolates) were rare and occurred only during transitional bloom periods. C_LIO_LIResults suggest that zooplankton communities may be adapted to cyanobacterial blooms, even when dominated by toxic species. C_LI

ecology↗
bioRxiv2025

Warm-loving species perform well under limiting resources:trait combinations for future climate

Ecosystems are warming alongside shifts in other abiotic factors, leading to interactive effects on populations and communities. This underscores the importance of studying how organisms respond to multiple environmental changes simultaneously. In aquatic ecosystems, as surface waters of lakes and oceans warm, longer and stronger periods of thermal stratification lead to changes in resource (light and nutrient) availability. We investigate the combined effect of temperature and resource availability on 19 populations (comprising 17 species) of freshwater phytoplankton to examine how temperature influences the minimum resource requirements (and Monod parameters) for light, nitrogen, and phosphorus. We also evaluate how resource availability affects each populations thermal traits (i.e. thermal performance curve -TPC-parameters). When averaged across all populations, the requirements for light and phosphorus tended to display a U-shaped relationship along temperatures. Individual populations varied greatly in their responses to temperature, leading to shifts in the identity of the best competitor across the thermal gradient, particularly for nitrogen and phosphorus. TPC responses to resource limitation were highly variable, but thermal optima and maxima of individual populations often decreased with resource limitation, and thermal breadths (range where growth is 80% or more of its maximum) often increased due to a flattening of TPCs. Across all populations and resource types, the maximum optimum temperature across resource levels (maximum Topt) tended to be positively correlated with the temperature at which they had the lowest resource requirements (minimum R*). However, the temperature at which populations were the best competitors tended to be [~]5 {degrees}C colder on average than the temperature at which they grew the fastest. The populations with the highest thermal optima also had the lowest minimum resource requirements. Our findings reveal trait associations suggesting that some taxa already exhibit trait combinations that would support high performance under future warm and resource-limited conditions.

ecology↗
bioRxiv2025

Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases

Determining a genes functional significance within a cellular context has long been a challenge, as absolute expression level is an unreliable indicator. We introduce SIGnature, a framework for scoring gene importance by leveraging attributions derived from single-cell RNA-sequencing (scRNA-seq) foundation models. Attribution scores reduce technical noise, emphasize regulatory genes, and facilitate cross-dataset comparison - a core challenge for scRNA-seq analyses. We developed the SIGnature package as a tool for generating and querying attributions, enabling rapid gene set searches across massive scRNA-seq atlases. We demonstrated its utility using the MS1 monocyte signature, a poorly understood gene program activated in severe COVID-19 and sepsis. Searching 400 studies revealed novel associations between the MS1 signature and multiple hyperinflammatory conditions, including Kawasaki disease. Experimental validation confirmed Kawasaki disease patient serum induces the MS1 phenotype. These findings highlight that SIGnature can uncover shared mechanisms across conditions, demonstrating its power for large-scale signature scoring and cross-disease analysis.

bioinformatics↗
bioRxiv2025

Biotic interactions shape the realised niche of toxic cyanobacteria

Cyanobacterial blooms increasingly threaten vital freshwater ecosystems, with harmful impacts exacerbated by climate change and eutrophication. Despite extensive research on temperature and nutrient effects, our predictive capacity remains limited. We propose that this limitation stems from insufficient understanding of how biotic interactions modify cyanobacterial responses to abiotic conditions. Using five years of daily monitoring data from a eutrophic lake and state-space reconstruction modelling, we show that interactions with co-occurring plankton species fundamentally reshape the realised niche of bloom-forming cyanobacteria. Biotic interactions shift temperature thresholds by up to 13{degrees}C and phosphorus requirements by over 20 g/L--effects substantial enough to determine whether environmental conditions support or prevent blooms in Microcystis and Dolichospermum. Grazing inhibits bloom formation across cyanobacterial taxa, while facilitation by other phytoplankton may allow blooms at unexpectedly low temperatures and phosphate concentrations. These findings address a fundamental research gap--how species interactions shape realised niches in natural systems--while offering practical insights for bloom management. By integrating biotic interactions into monitoring programs and predictive models, we can improve forecasting accuracy and develop targeted interventions that complement traditional nutrient control approaches. These findings parallel recent advances in ecology suggesting the fundamental role of biotic interactions in mediating species responses to environmental change.

ecology↗
bioRxiv2025

Five years of high-frequency data of phytoplankton zooplankton and limnology from a temperate eutrophic lake

This study presents a comprehensive dataset from Lake Greifen, Switzerland, collected between April 2018 and June 2023, using high-frequency automated monitoring systems. The dataset integrates meteorological data, nutrient chemistry, water column profiles for water physics, and plankton underwater imaging, offering insights into the lakes physical and biological processes. A dual-magnification dark field underwater microscope captured hourly plankton dynamics at 3 m depth, providing size, shape, and taxonomic information. A profiler with a multiparametric probe monitored water temperature, oxygen, and other key parameters from 1 to 17 m depth, while weekly nutrient sampling complemented the measurements. Data processing involved rigorous cleaning protocols to remove technical artefacts, ensuring data quality. Our dataset showcases the utility of integrating different approaches for high-frequency monitoring to detect lake temporal processes, from phytoplankton blooms to zooplankton vertical migration and seasonal shifts in water column stability. This dataset provides a unique resource for studying limnology and plankton community ecology. All data and related processing codes are publicly available for further research, supporting interdisciplinary studies.

ecology↗
bioRxiv2025

Octopamine regulates neural circuits in the mushroom body and central complex, influencing sleep and context-dependent arousal.

Sleep is a complex and ubiquitous phenomenon in the animal kingdom, yet the mechanisms, modes, and effects of sleep on the brain and body remain highly variable and not fully understood. While sleep and wakefulness are often measured as two binary states at the behavioral level, animals exhibit a wide range of arousal states during wakefulness. Behaviors such as feeding, courting, escaping predators, or avoiding unfavorable environments are critical for survival and often compete with sleep. Biogenic amines, including dopamine, norepinephrine, and serotonin, are known to regulate sleep and arousal behaviors across species, offering valuable insights into how these states are co-regulated. In this study, we leverage the small number, discrete organization, and well-defined connectivity patterns of neuromodulatory neurons in the fly brain to investigate how specific octopamine (OA) neurons regulate sleep and context-dependent arousal. We focus on a pair of OA neurons, VPM3, which project extensively to the mushroom body (MB) and central complex (CX). Our findings reveal that VPM3 neurons are sexually monomorphic and that their activity is essential for sleep suppression and male courtship behavior. Furthermore, we demonstrate that the male-specific form of the fruitless gene in these neurons plays a critical role in sleep regulation and that their activity is influenced by sleep history. Using connectome data and highly specific genetic tools, we identify upstream inputs to VPM3 neurons from the CX and elucidate the downstream pathways mediated by the MB, as well as the role of specific OA receptors. These detailed investigations highlight the multifaceted role of octopamine in sleep suppression and context-specific arousal, providing a crucial link between identified sleep microcircuits in the mushroom body and central complex.

neuroscience↗
bioRxiv2024

G-CSF and IL-6 drive myeloid dysregulation during severe viral infection

Dysregulated myeloid states are associated with disease severity in both sepsis and COVID-19. However, their relevance in non-COVID-19 viral infection, the factors driving their induction, and their role in tissue injury remain poorly understood. We performed a meta-analysis of 1,622,180 myeloid cells from 890 COVID-19 or sepsis patients and controls across 19 published blood scRNA-seq datasets, which revealed severity-associated gene programs in both neutrophils and monocytes pointing to emergency myelopoiesis (EM). Using published bulk transcriptional data from 562 individuals with non-COVID-19 viral disease, we show that these signatures are similarly upregulated during severe influenza and RSV infection. Analysis of transcriptional and proteomic responses in tocilizumab-treated COVID-19 patients show that IL-6 signaling blockade results in a partial reduction of EM signatures and a compensatory increase in the growth factor G-CSF. Using a cellular model of human myelopoiesis, we show that both IL-6 and G-CSF stimulate the production of myeloid cells that express EM signatures in vitro. Using a mouse model of severe influenza infection, we demonstrate the effect of IL-6 and G-CSF signaling blockade on EM-associated myeloid cells, and highlight the opposing effects of EM-induced neutrophils and monocytes on tissue injury. Our study demonstrates the link between systemic cytokines and myeloid dysregulation during severe infection in humans, and highlights the cooperative role of IL-6 and G-CSF signaling in driving infection-induced myelopoiesis.

immunology↗
bioRxiv2024

Laboratory application of the Aquascope approach of automated imaging and classification for long-term plankton monitoring

Anthropogenic changes such as climate change and pollution have strong effects on plankton and its ecosystem services. In freshwater, phytoplankton forms the basis of the food web and plays a key role in water quality. It is therefore important to monitor the plankton community. In Switzerland, lake plankton has been monitored for decades by cantonal authorities. But in the future, there will be a limitation in the availability of trained taxonomists that are able to count plankton samples under the microscope as well as time and budget constraints. New technologies will be needed to fulfil the federal requirements on the monitoring of lakes in the future. Here we focus on two such instruments, both based on plankton automated imaging: the FlowCam and the Aquascope. The first is a commercially available instrument, the second is custom made. They are the only automated imaging instruments that can track freshwater plankton across the desired size range (phytoplankton and zooplankton). Their design makes them the state of the art technologies to make quantitative observations of plankton. While the FlowCam is a laboratory instrument, the Aquascope is originally designed for field deployment. In this report, we focus the empirical work on the laboratory application of the Aquascope approach of automated imaging and classification for long term plankton monitoring. We find that there are major advantages of the Aquascope approach but the application as a laboratory instrument still needs further development. The major advantages of the Aquascope approach compared to traditional, human-supervised, microscopy methods are the automation and the speed of the data processing, the availability of individual level traits and the management of the data generated. One of the major drawbacks is the lack of taxonomic resolution (mostly at the genus level). Nevertheless, we show that with a larger benchmarking project, it might be possible to continue the long term time series on a coarse taxonomic level as usually reported by cantonal authorities to the general public. We discuss advantages and limitations of Aquascope relative to traditional microscopy and FlowCam, and propose ways forward for future development and application of this approach.

ecology↗
bioRxiv2024

Automated plankton monitoring suggests a key role of microzooplankton and temperature for predicting dynamics of phytoplankton size classes

The interplay between abiotic (resource supply, temperature) and biotic (grazing) factors determines growth and loss processes in phytoplankton through resource competition and trophic interactions, which are mediated by morphological traits like size. Here, we study the relative importance of grazers, water physics and chemistry on the daily net accumulation rates (AR) of individual phytoplankton from natural communities, grouped into six size classes from circa 10 to 500 m. Using a Random Forest modelling approach and four years of daily data from a lake, we find that water temperature is generally a pivotal control of all phytoplankton AR. At the same time, nutrients and light are important for the smallest and the largest classes. Mesozooplankton abundance is a key predictor of the AR for small phytoplankton, with microzooplankton being important for the middle-size range. In our data, large and small phytoplankton have different (seasonal) blooming patterns: small forms are favoured by low temperature and grazing, and high phosphorus levels. Larger forms show positive ARs at high temperatures and low phosphorus (being relatively insensitive to zooplankton grazing). These results help us understand the opportunities and limitations of using size to explain and model phytoplankton responses to biotic and abiotic environmental change.

ecology↗
bioRxiv2023

Novel orthotopic model of neuroblastoma in RNU homozygous rats

Neuroblastoma, the most common extracranial solid malignancy in children, accounts for 15% of pediatric cancer deaths despite multimodal therapy including surgical resection. Unfortunately, complete surgical resection remains challenging due to encasement of major neurovascular structures, unclear tumor margins, and remote nodal disease. While mouse models of neuroblastoma are extremely valuable for studying tumor biology and medical treatments, the small size renders the mouse model insufficient to evaluate novel surgical therapy. Here, we have developed a novel rat model of neuroblastoma to facilitate further development of surgical treatment. Human neuroblastoma cells (SK-N-BE(2)) were injected into the adrenal gland of RNU nude rats. They developed 2 cm xenograft tumors at 5 weeks which were easily identifiable on MRI imaging and on visual inspection. The rats began losing weight and neared end stage at 7 weeks, at which point surgical resection was attempted. While surgical resection was technically feasible, the rats were too frail to survive surgery at the late stage. The pathology of the tumors was consistent with neuroblastoma: small round blue cells with strong PHOX2B staining. Thus, we present a novel rat neuroblastoma model that can be used for development of surgical techniques, such as the use of intraoperative contrast agents.

cancer biology↗
bioRxiv2021

Underwater dual-magnification imaging for automated lake plankton monitoring

We present an approach for automated in-situ monitoring of phytoplankton and zooplankton communities based on a dual magnification dark-field imaging microscope/camera. We describe the Dual Scripps Plankton Camera (DSPC) system and associated image processing, and assess its capabilities in detecting and characterizing plankton species of different size and taxonomic categories, and in measuring their abundances in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scale with the same measurements derived by traditional microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland), delivered images of plankton individuals, colonies, and heterospecific aggregates without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior at hourly timescales. The DSPC was able to track the dynamics of taxa in the size range between [~]10 m to [~] 1 cm, covering virtually all the components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances, despite imaging limitations in detecting small phytoplankton species and rare and large zooplankton taxa (e.g. carnivorous zooplankton). The most significant disagreements between traditional methods and the DSPC resided in the measurements of community properties of zooplankton, organisms that are heterogeneously distributed spatially and temporally, and whose demography appeared to be better captured by automated imaging. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and circadian fluctuations with a temporal frequency and morphological resolution that would have been impossible with traditional methods. We conclude that the DSPC approach is suitable for stable long-term deployments, and robust for both research and water quality monitoring. Access to high frequency, reproducible and real-time data of a large spectrum of the planktonic ecosystem might represent a breakthrough in both applied and fundamental plankton ecology.

ecology↗
bioRxiv2020

Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients

COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.

systems biology↗
bioRxiv2020

Induction of a regulatory myeloid program in bacterial sepsis and severe COVID-19

A recent estimate suggests that one in five deaths globally are associated with sepsis1. To date, no targeted treatment is available for this syndrome, likely due to substantial patient heterogeneity2,3 and our lack of insight into sepsis immunopathology4. These issues are highlighted by the current COVID-19 pandemic, wherein many clinical manifestations of severe SARS-CoV-2 infection parallel bacterial sepsis5-8. We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis or non-infectious critical illness, and validated its expansion in sepsis across thousands of patients using public transcriptomic data9. Despite its marked expansion in the circulation of bacterial sepsis patients, its relevance to viral sepsis and association with disease outcomes have not been examined. In addition, the ontogeny and function of this monocyte state remain poorly characterized. Using public transcriptomic data, we show that the expression of the MS1 program is associated with sepsis mortality and is up-regulated in monocytes from patients with severe COVID-19. We found that blood plasma from bacterial sepsis or COVID-19 patients with severe disease induces emergency myelopoiesis and expression of the MS1 program, which are dependent on the cytokines IL-6 and IL-10. Finally, we demonstrate that MS1 cells are broadly immunosuppressive, similar to monocytic myeloid-derived suppressor cells (MDSCs), and have decreased responsiveness to stimulation. Our findings highlight the utility of regulatory myeloid cells in sepsis prognosis, and the role of systemic cytokines in inducing emergency myelopoiesis during severe bacterial and SARS-CoV-2 infections.

immunology↗
bioRxiv2020

Arbitrary Boolean logical search operations on massive molecular file systems

DNA is an ultra-high-density storage medium that could meet exponentially growing worldwide demand for archival data storage if DNA synthesis costs declined sufficiently and random access of files within exabyte-to-yottabyte-scale DNA data pools were feasible. To overcome the second barrier, here we encapsulate data-encoding DNA file sequences within impervious silica capsules that are surface-labeled with single-stranded DNA barcodes. Barcodes are chosen to represent file metadata, enabling efficient and direct selection of sets of files with Boolean logic. We demonstrate random access of image files from an image database using fluorescence sorting with selection sensitivity of 1 in 106 files, which thereby enables 1 in 106N per N optical channels. Our strategy thereby offers retrieval of random file subsets from exabyte and larger-scale long-term DNA file storage databases, offering a scalable solution for random-access of archival files in massive molecular datasets.

bioengineering↗
bioRxiv2019

Early-Career Coordinated Distributed Experiments: Empowerment Through Collaboration

Coordinated distributed experiments (CDEs) enable the study of large-scale ecological patterns in geographically dispersed areas, while simultaneously providing broad academic and personal benefits for the participants. However, the effective involvement of early-career researchers (ECRs) presents major challenges. Here, we analyze the benefits and challenges of the first CDE exclusively led and conducted by ECRs (i.e. ECR-CDE), which sets a baseline for similar CDEs, and we provide recommendations for successful CDE execution. ECR-CDEs achieve most of the outcomes identified in conventional CDEs as well as extensive benefits for the young cohort of researchers, including: (i) receiving scientific credit, (ii) peer-training in new concepts and methods, (iii) developing leadership and communication skills, (iv) promoting a peer network among ECRs, and (v) building on individual engagement and independence. We also discuss the challenges of ECR-CDEs, which are mainly derived from the lack of independence and instability of the participants, and we suggest mechanisms to address them, such as resource re-allocation and communication strategies.

scientific communication and education↗