Biology Education

Department of Biology | Lund University

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Paleo-Physiology: The effect of Paleo-mimetic environments on aquatic fern species

Plants transitioned onto land approximately 500 million years ago. Since their transition to land, plants have undergone enormous morphological and molecular adaptation, to fit the terrestrial environment. During their long history on land, the Earth has also experienced many changes to its climate and atmosphere, including multiple mass extinctions, suggesting that the morphological and physiological process optimizations observable in plants today must be the effect of numerous rounds of evolutionary development that have fitted to different environments existing in the Earth‘s history. Ferns were the dominant land plant some 300 million years ago, with many lineages still successful in the present. This project aims to understand their optimizations to a changing atmosphere, by growing a set of aquatic ferns in conditions which mimic the environmental conditions present at various times in Earth’s history, in particular the Mesozoic era. This project will involve establishing an effective system to grow two species of aquatic ferns in the genera Azolla and Salvinia in paleo-mimetic atmosphere, in climate chambers, and investigating their functional response to these conditions at the physiological and molecular level. Results will be compared to extant preliminary data for conifers and angiosperms.

Methods used: Growth rate determination, aqua-culture, microscopy, pigment analysis, determination of cyanobacterial symbiont level by qPCR; with possibility of expanding into global omics approaches if a longer project is designed.

Most suitable background knowledge is a combination of plant ecophysiology and molecular biology. However, it is possible to adapt the project for candidates with more or less ecology or molecular cell biology.

Length of project: Flexible, a project of 30-60 credits can be designed.

Start date: To be discussed

Supervisor(s): Allan Rasmusson, Francois du Toit, Biology, LU

Please contact allan.rasmusson@biol.lu.se or stephanus_francois.du_toit@biol.lu.se

April 3, 2025

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Biology Molecular Biology

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Plant-Trichoderma interactions  

Project suggestions 

Supervisor(s): Allan Rasmusson, Bradley Dotson, Dept. Biology, LU 

 Many fungal species of the genus Trichoderma live in symbiosis with plant roots. The fungus produces substances that stimulate plant growth and immune system but also directly attacking other microorganisms, including pathogens. Therefore, some strains of Trichoderma have been used as biocontrol and biostimulants in agriculture, decreasing the need for agrochemical use. The effect of Trichoderma on plants is strongly dependent on the plant genome, which is involved in a mainly unknown intricate interaction with the fungus, likely involving exchange of several signalling biomolecules.  Plant genes that are essential for biostimulation and biocontrol by fungi can be used in breeding, to make plants that can better benefit from biocontrol and biostimulation. However, we presently do not know what genes these are.  

 One possible class of genes that are essential for positive symbiosis with fungi are plant genes encoding proteins that are needed for the plants to avoid being damaged by the Trichoderma. This fungus attacks other microorganisms by secreting enzymes and peptide antibiotics, including so called peptaibols, where alamethicin is the standard model example. This peptide also lyses plant cells, but cellulase secreted from the Trichoderma induces resistance to the alamethicin by modifying the composition of the plant plasma membrane. This process we have named CIRA, and it is likely important for plant symbiosis with Trichoderma, though direct evidence are lacking. We have isolated CIRA-deficient mutants for a range of Arabidopsis genes, indicating that a so far unknown response chain is active. The different mutants belong to the categories Gene expression, Cell wall modifying, Signalling, Membrane lipid modifying and “Unknown”.  

 We can design differently long projects (30-60 credits) at multiple levels: 

  • Whole plant level comparison of genetics of inbred sugar beet breeding lines as expressed in their biostimulation phenotypes. Includes work with molecular markers, genotyping and phenotyping on soil. 
  • Analysis of particular known Arabidopsis mutants, their (lack of) biostimulation by Trichoderma, and the potential involvement of calcium signalling. This will involve sterile plant growth, fluorescent microscopy and measurements using intracellular fluorescent reporters. 
  •  Identification and analysis of novel CIRA genes by mutant screening. Arabidopsis CIRA mutants are identified by a fluorescent phenotypic change and verified by designing PCR assays and analysing a second mutant allele for the same gene. The genes found are analysed in a first line by bioinformatic database mining (e.g. gene expression patterns, protein localisation, post-translational modification, etc). In a longer project additional analyses can be done. Acquired data will be used in order to assemble a preliminary signalling path. 

 For the sugar beet project, background knowledge on plant physiology, genetics and/or agriculture is suitable. For the Arabidopsis projects, background knowledge on plant physiology, molecular cell biology and molecular genetics is suitable. However, a project can usually be designed in accordance with the background of a candidate. 

 For more information and discussions please contact allan.rasmusson@biol.lu.se or bradley.dotson@biol.lu.se. 

April 3, 2025

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Biology

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Large scale histology-based image analysis in oncology

Determining the histological structure of tumors is important for understanding spatial tumor biology and to identify the pathological mechanisms underlying cancer. By analyzing tissue architecture, cellular organization, and interactions within the tumor microenvironment, researchers can gain insight into mechanisms behind, for example cancer recurrence, response to treatment and other clinically important features where prediction models are warranted.

The project proposal

The last couple of years have focused on deep learning models for analyzing images derived from biological tissue. There have been models trained to detect different cell type representations in H&E images. One is Hover-Net which both segments and classifies cells into normal epithelial, malignant/dysplastic epithelial, fibroblast, muscle, inflammatory, endothelial or miscellaneous (necrotic, mitotic and cells)1. Another software ConvPath uses a model to define lymphocytes, tumor cells, stroma cells and their regional border2. Detecting and identifying the different cells and regions enables downstream tasks such as investigation of tumour infiltrating lymphocytes (TILs). For example, TILs have proven to predict cancer recurrence3.

The proposed project will explore the different interactions/spatial metrics related to defined cell types, including cell to cell distances, cellular niches and correlate these with clinical parameters such as outcome or previously defined high-risk patient parameters. The goal is to profile and understand the TME better and to find patterns or structures that can be used to stratify patient’s tumor in more detail. The steps would be to identify cells in the tissue by segmentation, then further classify the cells to known cell types. The downstream task involves calculating the distance between cell types based on known metrics such as using the nearest neighbor distance, (Ripley’s) K-function (cross), pair correlation function, neighborhood analysis etc.

Data-set available for the project

The project will have access to HTX staining of duplicate tissues from 650 patients diagnosed with diffuse large B-cell lymphoma (DLBCL).  This is a unique clinical dataset with high potential for translational publications, as well as method development.

Methods

The project will evaluate different workflows for segmenting and classifying cells in DLBCL using python mainly because of the model implementations and Pythons image handling. To tailor the task to lymphoma, different models will be evaluated including HoLy-Net4, Hover-Net with the aim to extract spatial metrics from the full image dataset and to perform data integration with clinical data. Evaluation of the classification model will be performed based on previously available multiplex immunofluorescence data. Downstream statistical tasks can be done in R or Python.

Requirements

We seek a bioinformatic student that is proficient in R, and with basic knowledge of Python. You will have the possibility to deepen your experience in Python and gain hands-on experience on high-throughput image and down-stream data handling as well as data integration.

Principle investigator/supervisor: Sara Ek

Practical supervisor: Daniel Nilsson

Department of Immunotechnology, Lund University

Starting date: flexible, reach out at sara.ek@immun.lth.se to discuss your interest

Length/credits: (30-60 hp) the project can be adapted to fit as either course project or longer combined master thesis projects

References: previous students from the bioinformatic program include Teodor Alling, Mattis Knulst, Daniel Nilsson and Markus Heidrich. Two of previous students are today employed within the group.

 

Literature

  1. Graham, S., Vu, Q. D., Raza, S. E. A., Azam, A., Tsang, Y. W., Kwak, J. T., & Rajpoot, N. (2019). Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images. Medical image analysis58, 101563. https://doi.org/10.1016/j.media.2019.101563
  2. Wang, S., Wang, T., Yang, L., Yang, D. M., Fujimoto, J., Yi, F., Luo, X., Yang, Y., Yao, B., Lin, S., Moran, C., Kalhor, N., Weissferdt, A., Minna, J., Xie, Y., Wistuba, I. I., Mao, Y., & Xiao, G. (2019). ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. EBioMedicine50, 103–110. https://doi.org/10.1016/j.ebiom.2019.10.033
  3. Corredor, G., Wang, X., Zhou, Y., Lu, C., Fu, P., Syrigos, K., Rimm, D. L., Yang, M., Romero, E., Schalper, K. A., Velcheti, V., & Madabhushi, A. (2019). Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research, 25(5), 1526–1534. https://doi.org/10.1158/1078-0432.CCR-18-2013
  4. Naji, H., Sancere, L., Simon, A., Büttner, R., Eich, M. L., Lohneis, P., & Bożek, K. (2024). HoLy-Net: Segmentation of histological images of diffuse large B-cell lymphoma. Computers in biology and medicine, 170, 107978. https://doi.org/10.1016/j.compbiomed.2024.107978
March 27, 2025

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Bioinformatics

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How are solitary bee communities affected by farmland landscape composition?

Pollinating insects, such as wild bees, are declining worldwide, threatening pollination of both wild plants and agricultural crops. The main reason for these declines is intensive farming practices which leads to losses of nesting habitats and flowering food resources [1]. However, all species are not equally affected, with important consequences for which wild plant species or agricultural crops that may suffer pollination losses. This is because certain functional traits (e.g. morphological and life-history traits) make some species more vulnerable to landscape changes than others [2]. Information on which traits make species vulnerable may aid conservation of declining species, by for example, suggesting interventions that match species nesting and foraging preferences or mobility.
This project takes a landscape perspective on bee conservation by investigating how habitat availability and landscape scale complexity influence solitary bee communities.

Potential research questions are, for example:
– How is local bee abundance and diversity affected by local and landscape scale habitat availability?
– How do bee traits interact with habitat availability at local and landscape scales to shape bee communities?
– Is habitat availability (amount) or landscape characteristics most important in moderating bee community composition?

Methods
You will use existing data on cavity nesting bees, flower surveys and land-use data, collected in 54 sites across Scania, combined with data on bee traits. While there are straightforward research questions given by our landscape design, the project provides ample opportunities to analyse data in relation to research ideas developed by you. Depending on the research questions chosen, you will use methods such as GLMs and multivariate statistics. You may also extract additional spatial data on habitat availability using GIS.

Contact: Anna Persson (anna.persson@cec.lu.se) and Henrik Smith (henrik.smith@biol.lu.se)

References:

  1. Potts et al (2010) Global pollinator declines: trends, impacts and drivers. DOI: 10.1016/j.tree.2010.01.007
  2. De Palma (2015) Ecological traits affect the sensitivity of bees to land‐use pressures in European agricultural landscapes. DOI: 10.1111/1365-2664.12524
March 24, 2025

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Biology

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Effect of climate and urbanisation on hatching failure in Great and Blue tits

In recent decades, populations of many wild bird species have declined dramatically worldwide due to many factors associated with urbanisation. Climate change, induced by human activity, influence the population dynamics of wild birds due to its effect on behaviour, physiology, and reproduction. It was shown that in many wild bird species that not just the increasing temperature, but the unpredictable severe weather changes (i.e. immediate temperature drop, or snowing in April) can have a negative impact on nestlings´ growth or fledging success. Unfortunately, our knowledge about how hatching failure, as one of the main determinant of fitness, can change due to climate change, and how this effect is altered by urban environment (eg.: urban heat island effect), is scarce.

Aim of the study: Using our long-term dataset, we will to study, how temperature increase and extreme weather event influence hatching failure in 2 wild bird species (Blue and Great tits).

Questions:

Q1: Did hatching failure increase over the last decade?

Q2: Do the changes in hatching failure differ between urban and rural habitats?

Q3: Do the interaction between climate and urban environment influence hatching failure?

Your tasks:

  • Collect basic breeding data in 2025, following the individual breeding attempt, ringing nestlings and adults, collecting unhatched eggs.
  • Organise the data back till 2013 for your analysis.
  • Collect the weather data for each nestbox from different databases.
  • Carry out the statistical analysis.
  • Write your thesis.

You will learn to:

  • handle and measure birds
  • use brightfield and fluorescent microscope, fluorescent DNA staining of the egg perivitelline layer
  • basic principles of databases and using different statistical tools to analyse your data
  • use GIS for analysing spatial data

Starting date: 1st of April (but sooner is the better). Duration: 45-60 credits

Contact:

Main supervisor: Caroline Isaksson: caroline.isaksson@biol.lu.se

Co-supervisor: Zsófia Tóth: zsofia.toth@biol.lu.se

March 18, 2025

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Biology

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Pair bonding and breeding success in an urbanized word

Long-term pair bonds are common in many large long-lived bird species but do also occur in small short-lived passerines. Mate retention and ‘divorce’ have been regarded as two sides of a strategy to increase reproductive success in Great Tits and Blue Tits as both occur regularly in these species. Both biotic (eg. food availability) or abiotic (eg. weather) factors can influence if the pair stay together or divorce within or between breeding seasons. Urban environment differs from rural environment regarding both biotic and abiotic factors leading to the birds need to cope with different challenges. However, the birds may choose different pair bonding strategy in urban and rural habitats to increase their fitness, up to date there is no study that investigated the differences in pair bonding in urban-rural comparison and its effect on fitness.

Aim of the study: Using a long-term dataset back till 2013, the project aim to study if urbanisation influence pair bonding, and if pair bonding has a direct effect on breeding success of great and blue tits.

Questions:

  1. Is there any difference in pair bonding (and/or divorce rate) between urban and rural environments?
  2. Does air or/and noise pollution influence pair bonding (and/or divorce rate)?
  3. Does pair bonding (and/or divorce) influence hatching success, nestling size?

Your tasks:

  • Collect basic breeding data in 2025, following the individual breeding attempt, ringing nestlings and adults.
  • Organise the data for your analysis back till 2013.
  • Modelling climate, and pollution data
  • Carry out the statistical analysis.
  • Write your thesis.

You will learn to:

  • handle and measure birds
  • basic principles of databases and using different statistical tools to analyse your data
  • use GIS for analysing spatial data

 

Starting date: 1st of April (but sooner is the better). Duration: 45-60 credits

Contact:

Main supervisor: Caroline Isaksson: caroline.isaksson@biol.lu.se

Co-supervisor: Zsófia Tóth: zsofia.toth@biol.lu.se

 

 

 

March 18, 2025

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Biology

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Effect of anthropogenic pollution on hatching failure in Great and Blue tits

Pollutions from urban, industrial, and agricultural activities put ecological health at risk due to contamination and accumulation in wildlife and humans. Widespread effect of pollution, such as air and noise pollution, on animals have long been documented including its detrimental effect on physiology, reproduction and development. Growing evidences have shown that particulate matter, NOx and noise pollution are associated with impaired fetal development and adverse birth outcomes in human. Furthermore, it was shown in an experiment in zebra finches that the traffic noise can impair embryonic development leading to embryonic death. However, we know that anthropogenic pollution can trigger developmental failure, we do not know if it affects the natural populations or not.

Aim of the study: Investigate the effect of anthropogenic pollution on hatching failure rate and the cause of hatching failure (embryo death, fertilisation failure etc…) in Great and Blue tits (Parus major & Cyanistes caeruleus).

Questions: Does anthropogenic pollution (noise, particulate matter and NOx) influence hatching failure in natural populations?      

Your tasks:

  • Collect basic breeding data in 2025, following the individual breeding attempt, ringing nestlings and adults, collecting unhatched eggs.
  • Organise the data for your analysis for 3 years (2023-2025)
  • Collect the noise pollution data for each nestbox based on the measurements of Naturvårdsverket. You will use QGIS for this.
  • Carry out the statistical analysis.
  • Write your thesis.

You will learn to:

  • handle and measure birds
  • basic principles of databases and using different statistical tools to analyse your data
  • use GIS for analysing spatial data

 

Starting date: 1st of April (but sooner is the better). Duration: 45-60 credits

Contact:

Main supervisor: Caroline Isaksson: caroline.isaksson@biol.lu.se

Co-supervisor: Zsófia Tóth: zsofia.toth@biol.lu.se

March 17, 2025

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Biology

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How do mycorrhizal fungi forage for resources in soil and how do different species interact with each other?

Arbuscular mycorrhizal fungi (AMF) form symbiosis with approximately 80% of land plants. The arbuscular mycorrhizal symbiosis has been extensively studied, however, most studies have been conducted from the perspective of the plant, and there is little known about the decision making and foraging behaviors of the fungi themself. In the soil, multiple AMF cohabit but little is known about how they interact with each other. Interaction between different species of fungi has been done on wood decomposers which unraveled some programmed cell death mechanisms. However, with AMF, it is difficult to study the interaction of two individuals due to their obligate biotrophy and very sparse mycelium.

In this project we will combine microfluidic soil chip systems with AMF symbiotic systems. The soil chips (developed in the team) are ideal for studying hyphal architecture and monitoring growth patterns of hyphae and mycelia over time. They can provide a useful tool to help us understand the hyphal behavior of AMF outside of plant tissues during the symbiosis. With this system we can measure how fungi forage for resources in a complex and microscopically heterogenous environment, and study their strategies implemented to explore their environment. We can also study the interaction between species at the micrometer scale and single out individual hyphae to gain insight into how fungal tips respond.

In the team, one species of AMF has been studied in soil chips (Hammer et al., 2024), but AMF form a very diverse group with very different morphological and physiological traits. It is therefore unknown if other AMF species behave the same way and present the same characteristics in the soil chip.

During this project you will be involved in all aspects of fsetting up and running the experiment, fabricating the soil chips, inoculating them, monitoring the fungal growth using microscopy and analyzing the images and results.

Duration: 45-60 cr MSc thesis

Contact: Ayla Mongés ayla.monges@biol.lu.se, Kristin Aleklett Kadish kristin.aleklett_kadish@biol.lu.se

March 15, 2025

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Biology

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Are mycorrhizal fungi calling the shots during symbiosis?

Arbuscular mycorrhizal fungi (AMF) form symbiosis with approximately 80% of land plants. The arbuscular mycorrhizal symbiosis has been extensively studied, however, there is little known about the decision making and foraging behaviors of the fungi themself. Marchantia paleacea is a liverwort and a model plant for studying the arbuscular mycorrhizal symbiosis. This plant has many advantages for this due to its size and ease of cultivation as well as the possibility to observe fungal colonization in its rhizoids. It also gives us a clue about how some of the first land living plants interacted with fungi to overcome the many stresses of colonizing land.

One of the reasons why the study of AMF is difficult is because they are obligate symbionts. They can survive only a few weeks after germination without a host plant.  In this project we will use a medium developed by Tanaka et al., 2022 that allow the autonomous growth of AMF. By growing AMF together with Marchantia on this particular medium or not, we can further assess the decision-making processes of the fungus.

During this project, you will be involved in all aspects of the experiment: setting the AMF cultures, growing them with Marchantia, inoculating the plants, monitoring the fungal growth and plant colonization using microscopy and images analysis of results.

Duration: 45-60 cr MSc project

Contact: Ayla Mongés ayla.monges@biol.lu.se, Kristin Aleklett Kadish kristin.aleklett_kadish@biol.lu.se

March 15, 2025

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Biology

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Comprehensive analysis of MYBs transcription factors across Solanaceae family

Transcriptional factors (TF) are vital regulatory elements that under certain conditions bind to DNA and alter the rate of gene transcription and expression (Latchman 1993). These transcriptional regulators therefore act as candidates for modification of complex traits in crop plants (Rabara et al. 2014). MYB transcription factors, characterized by an N-terminal “MYB” domain, are one of the largest and diverse TF families in plants. There are at least four types of structurally different MYB proteins in plants that control crucial biological processes such as biotic and abiotic stress, secondary metabolism, development and differentiation (Du et al. 2009; Dubos et al. 2010). The family Solanaceae includes several species of economically important, medicinal and horticultural crops worldwide (Shahzadi et al. 2015). However, no comprehensive analysis of the MYBs across the family has been conducted so far. Therefore, the proposed project will be an attempt to gain insight into the complexities of MYB family diversity, understand impacts of genome evolution on gene families and develop an evolutionary framework to understand the origin of various subcategories of MYB gene family. Methods involved will be identification of MYB homologs using the Sol genomics Portal database where 14 sequenced genomes are available. The homologues will be screened for the presence of functional MYB domain. All the homologues will be analyzed for constructing evolutionary relationships, their gene structure, physicochemical properties, protein structure etc. 

In this project the student will develop a strong foundation in plant molecular biology, bioinformatics, evolutionary genomics and plant evolution, gaining hands-on experience in analyzing transcription factor gene families using computational approaches. The data collected and the results of this project will provide a solid foundation for an independent scientific publication.

 

Please contact Sissi Lozada Gobilard (sissi.lozada_gobilard@biol.lu.se) for any questions or interest

March 11, 2025

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Bioinformatics Biology

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