LCLU Summer Placements

Background
Membrane-based structures such as lipid or fatty-acid vesicles are the compartments of choice when developing protocell models, owing to their similarity to extant cells. However, a more fundamental compartment model is based on peptide-nucleic acid coacervates, which resemble membraneless organelles formed via the liquid-liquid phase separation of RNA and proteins in modern cells. In a prebiotic nucleic acid-peptide world, phase-separating short peptides and nucleic acids may have formed coacervate protocells earlier than the more complex vesicular supramolecular structures. Protocells persisting over longer periods will have displayed survival fitness within the prebiotic environment, concentrating and propagating chemical components that would have played an important role in the development of more complex assemblies leading up to the genesis of the first cells.

Objectives 
The goal of this project is to investigate how two different populations of coacervate protocells evolve with time, both independently and as population mixtures. Each protocell population will have a different nucleic acid sequence – the proto-genome – which will govern protocell dynamics and stability (the phenotypic traits). This project aims to develop our understanding of how protocell assembly and survivability can be linked to a short oligonucleotide that serves as its “genome.”

Methodology
The coacervate protocells will comprise two components:  short peptides containing charged, amino acid residues, such as arginine, which would have been present on early Earth, and short, single-stranded DNA or RNA sequences. The protocells will be tested for stability in a range of conditions by varying the solution pH, buffer composition (imidazole vs. phosphate vs. HEPES), solution ionic strength, and temperature (to mimic freeze-thaw cycles). Two populations of protocells, each comprising a different oligonucleotide, will then be combined and monitored for stability by tracking encapsulated fluorescent dyes using confocal microscopy. To mimic dynamically changing early-Earth conditions, temperature, pH and solution ionic strength will be varied to induce coacervate instability. The effect of the destabilized coacervate population on the stable coacervates will be observed to determine coacervate fitness.    

Research environment: This project will be carried out in the Protocell Lab of Prof. Claudia Bonfio, Associate Professor at the Department of Biochemistry and affiliated with the Yusuf Hamied Department of Chemistry. The lab is pioneering the development of dynamic prebiotic compartments including liposomes and coacervates capable of growth and replication. The lab’s recent work has shown that the sequence and composition of short peptide and nucleic acid strands dictate the stability of coacervate protocells. The student will have the opportunity to learn both physicochemical and biophysical experimental techniques and develop a broad understanding of the origins-of-life research within the context of functional prebiotic compartments.

Nucleosynthetic isotope anomalies reflect the heterogeneous distribution of material derived from diverse stellar sources across the early Solar System. These small isotopic variations preserved in meteorites reveal large-scale isotopic structures, most prominently expressed in the carbonaceous–non-carbonaceous (CC–NC) dichotomy between the inner and outer Solar System. This scenario is further complicated by variability within each reservoir, as well as transport and mixing between them, the magnitude and timing of which remain debated. Constraining how material was distributed over space and time is therefore fundamental to understanding the accretion histories and resulting compositions of planets, which form from these dynamically evolving reservoirs. 

This project will investigate multi-element nucleosynthetic isotope variability using a data-driven framework to examine how these variations developed through transport and mixing processes. Nucleosynthetic anomalies have been identified across elements with contrasting geochemical behaviour, volatility, and nucleosynthetic origins (e.g. Ca, Cr, Fe, Zn, Ru). However, different isotope systems frequently exhibit weak or decoupled relationships, indicating that the distribution of their carrier phases was spatially and temporally complex and not readily captured by simple mixing relationships. In addition, comprehensive multi-element datasets remain limited because high-precision isotope measurements are time- and resource-intensive and often constrained by available sample mass. As a result, different isotope systems have been measured in different subsets of meteorites, producing a fragmented record that obscures the underlying structure of isotopic variability. This project will therefore apply statistical and machine-learning approaches to identify recurring patterns across isotope systems and to quantitatively assess how isotopic variability is organised in space and over time. 

To achieve this, published compilations of nucleosynthetic isotope measurements (e.g. Astromat) will be assembled into a structured dataset suitable for joint statistical analysis. Exploratory data analysis and unsupervised approaches will be used to identify recurring modes of co-variation across isotope systems and across meteorite groups, highlighting coherent structures and mixing patterns in isotopic variability across the early Solar System. The same framework will then be used to compare patterns among meteorite groups with different formation ages to assess whether the governing transport and mixing dynamics changed over time. Together, these analyses will help constrain the processes that shaped the distribution, isotopic variability, and availability of material during planetary formation. 

The internship will be structured over eight weeks: (1–2) compilation and organization of multi-element isotope data; (3–4) exploratory and unsupervised analysis to identify spatial structure; (5–6) analysis of variability across meteorite groups and their formation ages; and (7–8) integration of spatial and age-dependent patterns to interpret implications for early Solar System mixing and isotopic evolution. The project will be supervised by researchers with extensive experience in nucleosynthetic isotope systematics and early Solar System evolution, spanning analytical isotope geochemistry, interpretation of multi-element systematics, and quantitative geochemical modelling. 

Hydrogen Cyanide (HCN) is an abiotic precursor to animo acids and for the building blocks of life. Recently, the ExoMars Trace Gas Orbiter deduced an upper limit for HCN in Mars' atmosphere. One of the known ways in which HCN can form is via the oxidation of nitrogen under lightning conditions. Recently, the SuperCam microphone aboard the Perseverance rover has detected electric discharges in dust clouds on Mars. 

Most detections of discharges have occurred during the dusty season (Ls 200-360) over the past two martian years. The associated chemistry of such effects have not been studied before, nor the possibility of HCN production in present day Mars.

What the student will do
This project looks to derive a range of electrostatic pulses to inject as atomic N into a box model and analyse the results. The student will use a 0-dimension box model already set up under Mars conditions to test a variety of lightning scenarios under different dust storm events. The model will include a set of chemical reactions derived for the production of HCN. The student will run a set of electrostatic 'pulses' and analyse the production and destruction of HCN under different dust opacities to understand how the impact of dust optical depth influences this chemistry.

Student requirements
The student should have a background in Physical Natural Sciences (Physics or Chemistry), Computational Sciences or Statistics. Some familiarity with python or another interactive coding language is helpful but not necessary. They will use some terminal commands and will run a FORTRAN code, although no prior experience of this is needed.

References

• Chide, B., Lorenz, R.D., Montmessin, F., Maurice, S., Parot, Y., Hueso, R., Martinez, G., Vicente-Retortillo, A., Jacob, X., Lemmon, M. and Dubois, B., 2025. Detection of triboelectric discharges during dust events on Mars. Nature, 647(8091), pp.865-869.
• Trokhimovskiy, A., Fedorova, A.A., Lefèvre, F., Korablev, O., Olsen, K.S., Alday, J., Belyaev, D., Montmessin, F., Patrakeev, A. and Kokonkov, N., 2024. Revised upper limits for abundances of NH3, HCN and HC3N in the Martian atmosphere. Icarus, 407, p.115789

Water is usually assumed to be the solvent for life, but recent work by William Bains, Janusz Petkowski and Sara Seager (2024) has opened up the question of whether alternative solvents could in principle host life. Solvents have to be present in a natural environment to be able to host life, and so as a first step, the stability of solvents should be evaluated systematically in planetary context. Formamide is proposed as a candidate for an alternate solvent for life and its origins: it is polar, chemically versatile, and central to several laboratory prebiotic scenarios, including those explored by Raffaele Saladino, John D. Sutherland and several other prebiotic chemists. The key question, however, is not whether formamide chemistry can be made to work in controlled laboratory settings, but whether formamide can plausibly survive under realistic planetary conditions. If it is rapidly destroyed by ultraviolet radiation or destabilized by common geochemical environments, then both formamide-based life and sustained formamide-driven prebiotic scenarios become difficult to justify.

This project will focus specifically on the UV stability of formamide under a range of chemically relevant conditions. The student will carry out a set of controlled irradiation experiments on formamide–water mixtures, varying pH and the presence of salts such as phosphate, sulfate, carbonate, sulfite, and ferrocyanide. The aim is to determine how rapidly formamide is destroyed under different conditions, and whether particular geochemical environments stabilize or destabilise it. The outcome will be a clear experimental assessment of whether formamide can persist long enough, under plausible planetary UV fluxes, to act as a meaningful solvent or prebiotic medium.

This project would suit a student interested in origins of life, planetary environments, or laboratory chemistry. Some prior laboratory experience is desirable but not required.

De novo (new) mutations that arise in the parental germline are a fundamental source of genetic variation: they underpin long‑term evolutionary change, but in the short term they are a major cause of rare genetic disease. While parental age is a well‑established determinant of de novo mutation rate, the extent to which predictable environmental cycles, especially light and radiation, modulate germline mutagenesis remains unresolved. This project will test whether seasonal and longer‑term changes in sunlight‑related exposures predict (i) overall de novo mutation burden and (ii) shifts in the mutational spectrum.  A particular hypothesis motivating this work is that multi-year solar-activity (sunspot) cycles may subtly alter biologically relevant ultraviolet (UV) flux at the Earth's surface; related cyclicity has been well reported in melanoma incidence for many decades.

Working within the Genomics England Research Environment, we will analyse ~10,000 parent–offspring trios from the 100,000 Genomes rare‑disease cohort spanning a five‑decade proband age range. High‑confidence de novo single‑nucleotide variants and indels will be curated using established trio‑based filters and rigorous quality control. Mutational signatures (SBS/ID patterns) will be extracted using SigProfiler, with particular attention to UV‑associated signatures such as SBS7 subtypes. Each trio will be time‑stamped to approximate conception and gestational windows, then linked to UK environmental records capturing short term variation in ultraviolet‑B index, photoperiod (day length), and surface temperature and longer-term solar variability (international sunspot number and complementary irradiance proxies such as F10.7 cm flux or Mg II). Statistical analysis will combine generalised additive mixed models (to capture non‑linear exposure–response relationships) and harmonic decomposition (to quantify periodicity). Multinomial mixture modelling will be used to test for enrichment of UV-responsive signatures (e.g., SBS7 subtypes) during higher solar activity. Confounders (parental age, ancestry, sequencing platform, and geographic region) will be controlled using mixed effects and propensity weighting.

Student project plan (8 weeks): Week 1-2: orientation to the Genomics England Research Environment; reproduce variant QC and compile per-trio de novo counts; run signature extraction on a subset. Week 3-4: build the exposure lookup table, including sunspot-number time series and derived cycle-phase variables; perform exploratory visualisation. Week 5-6: fit baseline and cycle-aware models; evaluate sensitivity to lag assumptions and confounder control. Week 7-8: produce a short report and reproducible code notebooks for sharing within the secure environment. The Chronomic Medicine Group brings expertise in statistical genetics, mutational signatures, environmental time‑series analysis and reproducible computation in secure genomic data settings. Risks are low: all work is computational and conducted inside a secure environment with no export of identifiable data. Practical risks (compute time and data‑access delays) are mitigated by using existing group pipelines and established Genomics England workflows. Outputs will include reproducible pipelines and derived summary statistics to support future work on radiation‑linked mutagenesis and genetic risk.

The project has been approved by Genomics England and is available to view in the research registry (https://research.genomicsengland.co.uk/research-registry/search/) under project ID 1306.

Research proposal

One of the central open questions in origin-of-life research is the emergence of biological homochirality. While amplification mechanisms are well studied, the source of the initial asymmetry remains unresolved. Chirality-induced spin selectivity (CISS) — the coupling between molecular handedness and electron spin — provides a plausible physical bias mechanism. Experiments show that chiral molecules interacting with metal surfaces can generate measurable spin polarization, yet the microscopic origin and chemical consequences of this effect remain debated. Recent theoretical work suggests that small relativistic spin–orbit interactions may be amplified through electron–electron Coulomb exchange, producing spin polarizations of experimentally relevant magnitude.

This project will explore whether spin-selective electron transfer at mineral or metal surfaces could have influenced reaction pathways relevant to prebiotic chemistry.

Objectives
To model spin-dependent adsorption and electron transfer of simple prebiotically relevant chiral molecules (e.g., small carbonyls or amino acid precursors) on transition-metal or mineral surfaces.
To quantify whether weak initial spin biases can be amplified through many-electron effects in realistic surface–molecule systems.
To assess whether resulting spin polarization could plausibly influence reaction energetics or enantioselective stability under early Earth conditions.

Methodology
The student will perform ab initio electronic-structure calculations using Hartree–Fock and density functional theory (DFT), with explicit treatment of spin polarization and spin–orbit coupling. Model systems will include small chiral organic molecules adsorbed on Cu(111) or Fe/Ni-containing mineral surface clusters relevant to prebiotic environments.

The project will proceed in stages:

• Construction and geometry optimization of molecule–surface complexes.
• Calculation of spin-resolved electronic structure with and without spin–orbit coupling.
• Analysis of spin density distribution, exchange contributions, and symmetry breaking.
• Exploration of reaction coordinates (e.g., electron transfer or bond activation) to determine whether spin polarization alters activation barriers or adsorption energies.

The student will use established quantum chemistry packages and analyse orbital structure and spin densities to identify amplification mechanisms. The work is computationally self-contained and feasible within a summer placement, while still addressing a conceptually significant question.

Supervision and Expertise
The project will be supervised by Bence Csakany (an LCLU funded PhD student) and Alex Thom whose research expertise lies in theoretical electronic structure, symmetry breaking in Hartree–Fock theory, and the microscopic origin of CISS well as the modelling of spin-dependent phenomena in molecule–surface systems and in interpreting symmetry-broken mean-field solutions in a physically meaningful way.

Hydrogen cyanide (HCN) chemistry is widely regarded as one of the most promising starting points for prebiotic synthesis. HCN is readily produced in reducing atmospheres, detected in interstellar environments, and predicted to be abundant on early Earth and exoplanets orbiting stars such as TRAPPIST-1. From simple oligomerisation and hydrolysis reactions, HCN-derived systems can generate amino acid precursors, nucleobases, and metabolic intermediates.

Despite this promise, a major unresolved challenge is whether HCN-based chemistry can spontaneously generate autocatalytic or self-sustaining reaction cycles under plausible planetary conditions. Many origin-of-life hypotheses rely on such cycles to drive chemical amplification and selection prior to true biological evolution. However, most proposed pathways are incomplete or rely on experimentally inferred networks without first-principles kinetic validation.

This project will focus specifically on testing whether a constrained HCN reaction network can produce emergent autocatalytic motifs when reaction energetics and kinetics are computed ab initio.
 

Objectives

1. Construct a minimal but chemically realistic reaction network for HCN oligomerisation and hydrolysis products (e.g., aminomalononitrile, formamide intermediates).
2. Compute reaction energetics and activation barriers for key elementary steps using density functional theory (DFT).
3. Derive rate constants via transition state theory.
4. Simulate network dynamics under varying temperature and concentration regimes.
5. Identify and characterise emergent autocatalytic loops using graph-theoretic metrics.

Methodology
1. Network Construction
The student will curate a tractable subset (10–20 species) of HCN-derived reactions from the literature. Automated reaction exploration tools may be used to suggest additional plausible elementary steps.
2. Electronic Structure Calculations
Geometry optimisations and frequency calculations will be performed using DFT. Transition states will be located and validated via intrinsic reaction coordinate (IRC) analysis. Selected reactions may be benchmarked using higher-level single-point corrections.
3. Kinetic Parameterisation
Activation free energies will be converted to rate constants using Eyring transition state theory. Environmental parameters (temperature range 250–350 K, implicit aqueous solvation) will be systematically varied.
4. Network Simulation
The student will implement deterministic rate equations to model time evolution of concentrations. Sensitivity analysis will identify rate-limiting steps and potential amplification pathways.
5. Topological Analysis
Using network science tools, the reaction graph will be analysed for feedback loops, strongly connected components, and autocatalytic motifs. The central research question is whether kinetic realism supports sustained chemical amplification.

Expected Outcomes

• A first-principles kinetic dataset for a minimal HCN prebiotic network.
• Identification (or falsification) of viable autocatalytic cycles.
• A transferable computational workflow for future origin-of-life modelling.

Supervisory Expertise

The project will be supervised by Tamara Buja (a PhD student working on reaction networks) and Alex Thom who together have experience of programming, quantum chemistry, kinetic modelling, and complex systems analysis.