Investigating Aureochrome Signaling in Nannochloropsis Algae

I am studying Nanochloropsis, a unicellular algae, to explore how it responds to tough environmental conditions like excessive light, cold temperatures, and freezing. My work centers on understanding the role of aureochromes—light-sensitive molecules—in helping Nanochloropsis survive these stresses. I’m particularly interested in how these algae adapt and what mechanisms they use to cope under different circumstances.

What I’m Investigating

To get a clear picture, I’m comparing several lines of Nanochloropsis: the normal, wild-type version and mutants with altered aureochromes. One key aspect of my research is testing how different daily light schedules affect their stress tolerance. Specifically, I expose some samples to 8 hours of light per day and others to 12 hours of light, then observe how well they handle intense light, cold, and freezing conditions. This helps me see if the amount of light they get each day changes their resilience. On top of that, I’m diving deeper into the molecular level by using RNA sequencing. This technique lets me identify which genes are regulated by aureochromes under a standard cycle of 12 hours of light and 12 hours of dark. By doing this, I can uncover what aureochromes do in everyday conditions, not just during stress, and get a better sense of their overall role in Nanochloropsis.

The Key Questions

• How does daily light exposure impact stress tolerance? I want to know if the amount of light Nanochloropsis gets each day—say, 8 hours versus 12 hours or 40 µE vs 400 µE—affects its ability to withstand harsh light, cold temperatures, or even freezing.

• What do aureochromes do under stress? I’m trying to figure out how these light-sensitive molecules help Nanochloropsis survive environmental challenges and whether their role changes depending on the light schedule.

• Which genes are under aureochrome control? By looking at the standard 12-hour light and 12-hour dark cycle, I’m mapping out which genes aureochromes turn on or off, giving me clues about their broader function in the algae.

Enhancing Long-distance Sucrose Transport in Plant

The research aims to unravel the mysteries of phloem loading in Arabidopsis, focusing on the role of the AtSWEET11 transporter in sucrose transport. By engineering bundle sheath cells to express AtSWEET11 using PULSE optogenetic tools, I hope to enhance long-distance transport and test whether this mimics the efficiency seen in maize. Simultaneously, through EMS mutagenesis, whole-genome sequencing, and RNA sequencing, I’m identifying the key genes and regulators that govern assimilate allocation, particularly in phloem parenchyma cells.

Why This Matters

What drives me is the chance to boost plant productivity. Phloem loading is a bottleneck in plant growth: if sugars don’t move efficiently, plants can’t grow well or produce enough seeds, especially under tough conditions like drought or poor soil. While Arabidopsis is a lab plant, what I learn here could apply to crops like wheat or rice. If we can enhance sugar transport, we might increase crop yields and make them more resilient—crucial steps toward sustainable agriculture in a world facing climate change and food security challenges. There’s still so much we don’t know about how plants regulate this process, and my work aims to fill those gaps.

The Key Questions

• Can expressing AtSWEET11 in bundle sheath cells enhance sucrose transport in Arabidopsis? I want to know if turning on this transporter in a specific spot improves how much sugar gets moved and how fast it happens.

• How do light-controlled changes in AtSWEET11 expression affect phloem loading dynamics? Using PULSE, I can switch AtSWEET11 transcription on and off with light. I’m curious how this fine-tuned control changes the timing and efficiency of sugar loading into the phloem.

• Which genes regulate AtSWEET11 and AtSWEET13 activity, and how do they shape assimilate partitioning? AtSWEET13 is another transporter similar to AtSWEET11. Through my mutagenesis and sequencing, I’m hunting for the genes that control both, and how they decide where sugars (or “assimilates”) go in the plant—whether to roots, seeds, or elsewhere.

Deep Learning for Single Cell Analysis Framework on
Scientific Compute Cluster

The Deep Learning for Single Cell Analysis (DANCE) framework is an advanced platform designed to harness deep learning techniques for tackling intricate tasks in single-cell analysis, such as cell clustering, type identification, and multimodal data integration. To meet the growing demand for evaluating and comparing computational models in this field, we have created a benchmark platform that enables researchers to reproduce and assess various models with ease. Hosted on GWDG's High-Performance Computing (HPC) Scientific Compute Cluster (SSC), this platform is delivered as a service, allowing customers to perform their analyses efficiently without the need to manage complex computational resources.

By integrating DANCE into the SSC, we enable researchers to tap into the cluster's powerful computational resources, running large-scale, computationally intensive analyses with ease. This eliminates the need for individual scientists to manage their own complex computing setups, streamlining workflows and boosting efficiency. Furthermore, this incorporation fosters a collaborative ecosystem where standardized tools and shared resources enhance reproducibility and comparability across studies. Ultimately, embedding DANCE within GWDG's HPC infrastructure empowers the scientific community to accelerate discoveries and advance breakthroughs in the life sciences.

Natural Selection on Deprecated Traits of Self-fertilizing Species

The research examines how environmental variability drives flower size evolution in Arabidopsis thaliana, a self-pollinating plant. By leveraging this model species, I explore how climatic gradients influence resource allocation tradeoffs, shaping predictable patterns of phenotypic and molecular evolution. Surprisingly, I uncover significant flower size variation across its range, highlighting the impact of local conditions on evolutionary outcomes. This work combines quantitative genetics, population genomics, and niche modeling to reveal these patterns.

Why This Matters:

Understanding how environmental differences fuel phenotypic diversification is key to predicting how species adapt to climate change and shifting habitats. My research upends assumptions about resource allocation in selfing plants, showing flower size varies spatially due to localized selection pressures. These insights extend beyond Arabidopsis, offering a lens to study evolutionary constraints and adaptability in other species under environmental stress.

The Key Questions: 

• How do climatic gradients across the range of Arabidopsis thaliana shape the evolution of flower size, and what role do they play in establishing predictable patterns of phenotypic variation? 

• What drives the observed variation in flower size through resource allocation tradeoffs, and how do these tradeoffs differ between favorable and resource-limited environments?  

• How do mutations with low pleiotropy—those affecting specific traits without broader impacts—influence flower size under diverse environmental conditions, and what does this reveal about the genetic architecture of adaptation?  

• Why does flower size shrink at the species’ climatic boundaries while remaining diverse at the center of its distribution, and what does this spatial pattern tell us about the balance between selection and genetic drift?

Molecular Characterization of Involved Amino Acid Permeases in Phloem Loading

The research investigates the role of Amino Acid Permeases (AAPs) in tomato plants (Solanum lycopersicum L.), which transport amino acids across cellular membranes to distribute nitrogen (N) throughout the plant. We conducted gene expression analyses in young/matured leaves, young/matured fruits, and roots of four tomato cultivars with contrasting Nitrogen Use Efficiency (NUE) under varying N supply levels. Our focus is on understanding how AAPs contribute to phloem loading and N partitioning, key processes influencing yield and fruit quality, especially under N-limited conditions compatible with sustainable agriculture.

Why This Matters:

Efficient nitrogen use is critical for crop productivity, yet excessive fertilizer application harms the environment and increases costs. By unraveling how AAPs regulate amino acid transport in tomatoes, this study aims to enhance NUE, enabling the development of cultivars that thrive with reduced N inputs. This advances sustainable agriculture, supports food security, and minimizes ecological damage, making it a vital step toward resource-efficient farming.

The Key Questions:  

• Which AAP genes drive amino acid phloem loading in mature leaves and unloading in fruits during the reproductive stage, and how do they affect N partitioning for yield and quality?

• How does the expression of the tomato AAP gene family vary with N supply levels, and do these patterns differ across cultivars with high versus low NUE?

• Can we pinpoint specific genes or quantitative trait loci (QTLs) linked to N transport to accelerate breeding of tomato varieties optimized for low N input agriculture?

Stress Physiology of Stipa caudata in Response to Salinity and Drought

This study explores how Stipa caudata responds to salinity and drought stress. We employ spectrophotometry to perform a detailed biochemical analysis, examining secondary metabolites and ions such as proline, methanol, malondialdehyde, sugar, phenolics, flavonoids, chlorophylls, and various ions. Additionally, we assess soil-based drought models to investigate their effects on plant morphology. The aim is to understand the physiological and biochemical adaptations that enable this species to withstand harsh conditions.

Why This Matters:

Understanding plant responses to environmental stress is essential for advancing sustainable agriculture, particularly as climate change increases salinity and drought challenges. This research could guide the development of stress-tolerant crops, enhancing food security and reducing agricultural losses in tough environments. It offers practical insights for eco-friendly farming practices.

My Key Questions:  

• Which biochemical pathways does Stipa caudata activate to cope with salinity and drought stress, and how do these pathways support its adaptation?

• How do soil moisture changes, as tested in our drought models, influence the plant’s growth and morphological development?

• Could the stress-response mechanisms uncovered in this study be applied to improve crop resilience in saline or water-scarce regions?