Grants Database

The Foundation awards approximately 200 grants per year (excluding the Sloan Research Fellowships), totaling roughly $80 million dollars in annual commitments in support of research and education in science, technology, engineering, mathematics, and economics. This database contains grants for currently operating programs going back to 2008. For grants from prior years and for now-completed programs, see the annual reports section of this website.

Grants Database

Grantee
Amount
City
Year
  • grantee: The University of Chicago
    amount: $2,500,000
    city: Chicago, IL
    year: 2022

    To build, from non-living chemicals, a minimal living system capable of reproduction and Darwinian evolution

    • Program Research
    • Sub-program Matter-to-Life
    • Investigator Jack Szostak

    This grant funds an ambitious plan by an international collaboration of six laboratories to achieve a milestone that science, and humanity more generally, has imagined for quite some time: building some version of life from scratch. That claim must be qualified by cautions that the effort may not succeed and by clarification that the proposed entity is probably better viewed as a minimal form of life rather than as a (much more complex) natural cell. To be clear about the version of life herein proposed, the goal of this project is to design and build a protocell from nonliving chemicals that is capable of indefinite cycles of genetic replication, growth, and division, and which—over generations—exhibits environmentally driven Darwinian evolution.The project team is led by Jack Szostak, Professor of Chemistry at the University of Chicago and includes researchers Irene Chen (UC Santa Barbara. U.S.), Sheref Mansy (University of Alberta, Canada), Arvind Murugan (University of Chicago, U.S.), John Sutherland (Medical Research Council, United Kingdom), and Anna Wang (University of New South Wales, Australia).Project activities will consist of laboratory experiments guided by theory and computation, organized along three primary research thrusts.First, the team will conduct research to achieve indefinite cycles of RNA replication by achieving high-fidelity copying of the entire RNA-based genome. The two major components of this first thrust are optimizing the chemistry for copying a given gene sequence from a template and ensuring that the entire genome is copied. The second research thrust focuses on achieving indefinite cycles of cell growth and division. Here the primary challenge is understanding and controlling membrane growth and division, and the team will experiment with several different approaches to using fatty-acid vesicles as the primary protocell container. In the third research thrust, the research team will address issues associated with making the genetic and compartmentalization systems mutually compatible. After these major goals are achieved, the team will then observe this primitive living system over several generations as it increases in complexity, adapts and evolves, and as its genome grows to encode more information about the world.

    To build, from non-living chemicals, a minimal living system capable of reproduction and Darwinian evolution

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  • grantee: University of California, Berkeley
    amount: $299,987
    city: Berkeley, CA
    year: 2022

    To explore how intentional and random mutations alter the swarming behavior of the model bacterial organism Proteus mirabilis

    • Program Research
    • Sub-program Matter-to-Life
    • Investigator Karine Gibbs

    Understanding how cells cooperate to achieve new capabilities is important since cooperation underlies the transition from single-cell life to multicellularity. This grant supports a series of experiments by Karine Gibbs, a Professor of Biology at the University of California, Berkeley, aimed at improving our understanding of the mechanisms that facilitate collective migration (swarming behavior) of the model bacterial organism Proteus mirabilis (P. mirabilis). Understanding the swarming behavior of P. mirabilis may eventually reveal fundamental principles for forming and possibly manipulating biological collectives.Professor Gibbs' work focuses on studying the role kin-recognition plays in P. mirabilis swarming behavior. Kin-recognition is a form of intercellular communication that relies on direct cell-to-cell contact. A filament carrying a toxin at its tip extends through the membrane of a P. mirabilis bacterium and punctures a neighbor's membrane, thereby delivering the toxin to the neighbor. If this neighbor-cell is genetically the same as the 'attacking' cell (i.e. it's a relative, kin) then the neighbor cell encodes the toxin as well as the antidote and the cell lives. If, however, the neighbor is not kin, then it does not encode the toxin nor the antidote and the neighbor dies.Prior studies by Professor Gibbs suggest that kin-recognition plays a role in P. mirabilis swarming and here she will use this model organism to study how collective migration is modified by two loosely-related mechanisms: intentional mutations affecting kin-recognition, and random mutations acted on by fitness-guided selection. Gibbs will leverage her prior work that correlates growth conditions with bacterial colonies exhibiting different levels of collectivity. Specifically, by varying bacterial growth conditions Gibbs is able to create two types of bacterial communities corresponding to fast/cooperative collective migration on the one hand and slow/independent migration on the other. Professor Gibbs will use her recipes for creating fast and slow swarming communities to pursue a research project with three aims.Under Aim 1, she will develop quantitative, physical metrics that can be used to distinguish fast-swarming colonies from slow-swarming colonies. Experiments involving microscopy and subsequent image-analysis will establish quantitative descriptors of cell morphology, physiology, and motility for both single-cells and for the cell-groups observed to facilitate fast swarming. Quantitative descriptors will be developed both for single-cells and for cell-groups in both fast and slow colonies. Potential descriptors include cell area, curvature, instantaneous speed, location and trajectory, adjacency to other cells, and the number of interactions over time, among others.Under Aim 2, Gibbs will use the quantitative descriptors developed in Aim 1 to assess whether and how mutations affecting kin-recognition influence collective migration. Experiments will be performed for two 'environments': growth conditions that enable fast/cooperative swarming and growth conditions that inhibit fast/cooperative swarming (thereby favoring slow/independent migration). The experimental approach involves comparing 'regular', unmutated P. mirabilis to P. mirabilis strains with mutations that disrupt the toxin secretion system used in kin-selection. This will allow Gibbs to test the hypothesis that kin-recognition provides a fitness advantage in environments where efficient swarming is possible but not in environments where independent behaviors dominate (efficient swarming not possible).Under Aim 3, Professor Gibbs will perform experiments intended to identify genes that promote collective fitness; specifically, the ability to participate in efficient swarming. Random mutations arise at some frequency and if you start with a mutant P. mirabilis that can grow but not swarm, the bacterial population will increase (growth) but will largely be constrained to its initial location (no swarming migration). As the number of bacteria increases, eventually a mutant cell will arise that has acquired a mutation that restores the ability to swarm. This mutant will swarm away from the static population, identifying itself by spatial separation and thereby allowing experimenters to capture and genetically sequence this mutant. The researchers will then determine the genome-location of the swarm-enabling mutation as well as the alterations to the descriptors of collective vs. independent behavior.

    To explore how intentional and random mutations alter the swarming behavior of the model bacterial organism Proteus mirabilis

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  • grantee: Stanford University
    amount: $1,500,000
    city: Stanford, United States
    year: 2022

    To complete a model of E. coli that accounts for over 90% of the well-characterized gene content

    • Program Research
    • Sub-program Matter-to-Life
    • Investigator Markus Covert

    To complete a model of E. coli that accounts for over 90% of the well-characterized gene content

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  • grantee: University of Michigan
    amount: $335,327
    city: Ann Arbor, MI
    year: 2022

    To establish quantitative relationships between the maximum achievable sensitivity of any biochemical process and the thermodynamic forces driving that process

    • Program Research
    • Sub-program Matter-to-Life
    • Investigator Jordan Horowitz

    Research over the past few decades has revealed that many cellular processes require levels of accuracy and sensitivity that cannot be reached near equilibrium; living systems must exist far from thermodynamic equilibrium (TDE) in order to achieve the levels of sensitivity that allow them to survive.This grant supports research by Jordon Horowitz, Assistant Professor of Biophysics and Complex Systems at the University of Michigan, to improve our understand of living systems by studying the biochemical networks active within cells through the lens of thermodynamics. Horowitz will study broad classes of biochemical models in an effort to establish quantitative trade-offs (inequalities) between the maximum achievable sensitivity of any biochemical process and the thermodynamics driving that process. If successful, this line of research will improve our understanding of the factors constraining biological function while also revealing how closely living systems operate from the maximum achievable biochemical sensitivity. 'Sensitivity' here is being used as a flexible term intended to capture a range of bio-performance metrics such as the ability to discriminate between binding to chemical A vs chemical B, or the ability to determine whether there are few or many food molecules in the local environment.Horowitz’s research is divided into three sequential aims. In Aim 1, he will perform numerical analyses of comparatively simple models to gain insight into how network structure and thermodynamics constrain performance in simple biochemical networks. These models are too simple to represent actual cellular processes yet simple enough that numerical analysis of the available phase space is practical. Simulations will be used to study networks with varying topological structure and thermodynamic driving force in order to determine the maximum possible sensitivity, along with the model parameters that achieve that sensitivity. These numerical findings will be captured in a 'library of kinetic networks' classified by sensitivity, network topology, and thermodynamics. In Aim 2, Horowitz will attempt to use graphical methods and the Matrix Tree Theorem to mathematically (analytically) prove that these discovered limitations are in fact rigorous bounds. If successful, the result will be a set of mathematical inequalities that quantify fundamental limitations on sensitivity imposed by network structure and thermodynamic drive.In Aim 3, Horowitz will attempt to expand and apply these findings to more complicated models that have been developed to capture actual cellular process, including generalized ‘butterfly’ networks, the ‘ladder’ model of adaptation, and a generalized bacterial-flagellar-motor model.

    To establish quantitative relationships between the maximum achievable sensitivity of any biochemical process and the thermodynamic forces driving that process

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  • grantee: Harvard University
    amount: $1,500,000
    city: Cambridge, United States
    year: 2022

    To enable the safe analysis of private data by expanding both an open-source library of software tools as well as a growing community of users

    • Program Research
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economics
    • Investigator Salil Vadhan

    To enable the safe analysis of private data by expanding both an open-source library of software tools as well as a growing community of users

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  • grantee: Digital Public Library of America, Inc.
    amount: $750,000
    city: Boston, MA
    year: 2022

    To build and expand a centralized Wikimedia engagement program that will make 15 million culturally rich digital files from 1000 member institutions from DPLA available on Wikipedia, Wikimedia Commons and related sites

    • Program
    • Sub-program Special Initiatives
    • Investigator John Bracken

    This grant provides funding to expand a collaboration between the Digital Public Library of America, a national library composed of some 5000 member libraries, archives, and galleries across the country, and Wikipedia, the largest encyclopedia ever created. Launched with Sloan Foundation support in 2019, the collaboration allows the upload of digital files from DPLA member institution into Wikimedia Commons, Wikipedia’s archive of more than 60 million video, photo, and audio files.Since the collaboration began in 2019, 200 DPLA member institutions have uploaded more than 3 million files into the Commons. Funds from this grant support the expansion of this partnership, resulting in an anticipated five-fold increase in the number of participating DPLA members from 200 to 1000 and an estimated 15 million files uploaded to the Commons. Initial estimates predict that this upload will generate 15 million page views per month, a substantial increase for Wikimedia and an unprecedented boost for DPLA and its participating members.Grant funds will support the creation of a pipeline to more efficiently facilitate continued contributions by DPLA member institutions; marketing and outreach to DPLA network members to raise awareness and solicit new project partners; onboarding of new DPLA hubs to the pipeline; hosting of training workshops and other support to contributing institutions; making necessary software and technical upgrades to accommodate uploads of partner content; developing new reporting tools; and engaging in outreach to the Wikimedia community.The project will make DPLA the first national aggregator whose content will be systematically ingested into Wikimedia Commons, reaching millions of people and establishing a pathway to further access to tens of millions of media files for the benefit of anyone on the web. 

    To build and expand a centralized Wikimedia engagement program that will make 15 million culturally rich digital files from 1000 member institutions from DPLA available on Wikipedia, Wikimedia Commons and related sites

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  • grantee: Canadian Institute for Advanced Research
    amount: $500,000
    city: Toronto, Canada
    year: 2022

    To support an international research initiative on innovation, equity, and the future of prosperity

    • Program Research
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economics
    • Investigator Dan Breznitz

    What interventions can promote equitable economic growth in regions left behind by the tech boom? Regional economic development is an increasingly urgent challenge for Sloan, for the United States, and throughout the world. Scholarly research needs to address innovation, prosperity, opportunity, and equity as related. One book that takes this on is Innovation in Real Places by Dan Breznitz, Professor in the Munk School of Global Affairs and Public Policy at the University of Toronto. He documents how the vaunted success of places like Silicon Valley, Tel Aviv, and Taiwan has been good for only a very few males from the upper classes and bad for most everyone else. Regions that simply try to emulate existing tech hubs waste lots of time, money, talent, and energy. Understanding how a given area can find its own niche in the global production processes makes much more sense.Together with two co-directors, Breznitz now leads the Innovation, Equity, and the Future of Prosperity (IEP) program at the Canadian Institute for Advanced Research (CIFAR).  The program brings together an international group of researchers from economics, sociology, geography, engineering, robotics, and history to develop a new approaches to studying place-based innovation, prosperity, and opportunity.  Sloan funds will help support IEP program operations including regular research workshops. CIFAR will also award Catalyst Grants to fund novel research collaborations among IEP program participants.

    To support an international research initiative on innovation, equity, and the future of prosperity

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  • grantee: Vanderbilt University
    amount: $498,548
    city: Nashville, United States
    year: 2022

    To develop graduate certificate courses and a postdoc-to-faculty program in multimessenger astronomy as an expansion of the Fisk-Vanderbilt Bridge Program

    • Program Higher Education
    • Investigator Kelly Holley-Bockelmann

    To develop graduate certificate courses and a postdoc-to-faculty program in multimessenger astronomy as an expansion of the Fisk-Vanderbilt Bridge Program

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  • grantee: University of Toronto
    amount: $260,640
    city: Toronto, Canada
    year: 2022

    To study collaboration between software engineers and researchers on scientific open source projects and to pilot interventions for sustained engagement in software production practices

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Shurui Zhou

    To study collaboration between software engineers and researchers on scientific open source projects and to pilot interventions for sustained engagement in software production practices

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  • grantee: University of Massachusetts, Amherst
    amount: $499,972
    city: Amherst, United States
    year: 2022

    To diversify pathways from undergraduate to graduate education in computer science and engineering at UMass Boston and Amherst through faculty and student  professional development and inclusive mentoring

    • Program Higher Education
    • Investigator Nilanjana Dasgupta

    To diversify pathways from undergraduate to graduate education in computer science and engineering at UMass Boston and Amherst through faculty and student  professional development and inclusive mentoring

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