Microbial Ecology and Population Dynamics
Bacteria primarily exist within dense and complex communities, like biofilms or the gut microbiome, where they compete for limited space and resources. These microbial consortia display heirarchical levels of spatial patterning much like eukaryotic cells within macro-organisms. This organization, resulting from the complex dynamics of competitive and cooperative interactions, can lead to emergent properties of functional significance to the consortia as a whole.
We are studying the single-cell population dynamics of small microbial systems where fluctuations and stochasticity dominate, to better understand the strategies employed by bacteria to cooperate or compete with other bacteria.
Mechanics limits ecological diversity and promotes heterogeneity in confined bacterial communities,T. Ma, J. Rothschild, F. Halabeya, A. Zilman, and J. N. Milstein, Proceedings of the National Academy of Sciences 121 (20) e2322321121 (2024).
Spatial exclusion leads to "tug-of-war" ecological dynamics between competing species within microchannels,
J. Rothschild, T. Ma, J. N. Milstein and A. Zilman, PLoS Computational Biology 19(12): e1010868 (2023).
Single-Molecule Imaging and Optical 'Omics
Recent advances in optical imaging have been so dramatic that light microscopy can now be used to directly quantify protein or nucleic acid numbers, modifications and interactions. This has given rise to the new fields of ‘optical proteomics’ and ‘optical genomics’.
We are developing quantitative approaches to single-molecule microscopy that will help us to understand the organizational principles of cells by mapping out their internal structure and quantifying the intracellular abundance of proteins and nucleic acids. This information can uncover functional oligomerization by signalling receptors such as GPCRs or provide insight into stochastic varation among populations of bacteria.
Single-Molecule Counting Applied to the Study of GPCR Oligomerization,J. N. Milstein, D. F. Nino, X. Zhou and C. Gradinaru , Biophys. J. 121, 3175-3187 (2022).
An Expectation-Maximization Approach to Quantifying Protein Stoichiometry with Single-Molecule Imaging,
A. Boonkird, D. F. Nino and J. N. Milstein, Bioinformatics Advances 1, vbab032 (2021).
Estimating the Dynamic Range of Quantitative Single-Molecule Localization Microscopy,
D. Nino and J. N. Milstein, Biophys. J. 120, 3901-3910 (2021).
Nanoscopic Stoichiometry and Single-Molecule Counting,
D. Nino, D. Djayakarsana and J. N. Milstein, Small Methods 3, 1900082, (2019).
Molecular Counting with Localization Microscopy: A Bayesian estimate based on fluorophore statistics,
D. Nino, N. Rafiei, Y. Wang, A. Zilman and J. N. Milstein, Biophys. J. 112, 1777-1785 (2017).
Bioimage Analytics
With the advent of single-molecule localization microscopy (SMLM), images of cellular structure and organization can be acquired with visible light at a spatial resolution well surpassing the diffraction limit. SMLM is increasingly being employed in cells to image and quantitatively analyze various protein complexes forming tens to hundreds of nm assemblies, from membrane receptors to nucleosome bundles.
We are developing clustering algorithms for detecting and analyzing protein aggregates in SMLM datasets and have already applied the technique to study transcription factories within cell nuclei. The software package is currently made available on our lab website and, while it only works on 2-dimensional datasets, we will soon be releasing a more extensive version that directly clusters 3D SMLM data.
FOCAL3D: A 3-dimensional clustering package for single-molecule localization microscopy,D. Nino, D. Djayakarsana and J. N. Milstein, PLoS Computational Biology, 16(12): e1008479 (2020).
Fast Optimized Cluster Algorithm for Localizations (FOCAL): A spatial cluster analysis optimized for super-resolved microscopy,
A. Mazouchi and J. N. Milstein, Bioinformatics 32(5), 747–754 (2016).
Antimicrobial Therapy
With the continued rise in the number of reported cases of antibiotic resistance, a next-generation of therapeutics are needed. We collaborate with medicinal chemists to aid in the development of highly-specific and effective antimicrobials as well as ultra-sensitive bacterial sensors. We apply biophysical techniques and analyses to measure the effectiveness of these compounds on both individual bacteria and bacteria embedded within biofilms.
E. Hudson, C. Faylinn, I. R. Miranda-Lopez, J. N. Milstein, and A. A. Beharry, ChemPhotoChem, e202400164 (2024).
Highly Potent Photoinactivation of Bacteria Using a Water-Soluble, Cell-Permeable, DNA-Binding Photosensitizer,
E. M. Digby, T. Ma, W. R. Zipfel, J. N. Milstein and A. A. Beharry, ACS Infectious Diseases 7, 3052–3061 (2021).
Sensitive Detection of Broad-Spectrum Bacteria with Small-Molecule Fluorescent Excimer Chemosensors ,
A. Cabral, N. Rafiei, E. de Araujo, T. Radu, K. Toutah, D. Nino, J. N. Milstein, D. Kraskouskaya and P. Gunning, ACS Sensors 5, 2753−2762 (2020).