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1.
J Theor Biol ; 357: 123-33, 2014 Sep 21.
Artículo en Inglés | MEDLINE | ID: mdl-24799131

RESUMEN

We present a computer simulation of group selection that is inspired by proto-cell division. Two types of replicating molecules, cooperators and defectors, reside inside membrane bound compartments. Cooperators pay a cost for other replicators in the cell to receive a benefit. Defectors pay no cost and distribute no benefits. The total population size fluctuates as a consequence of births and deaths of individual replicators. Replication requires activated substrates that are generated at a constant rate. Our model includes mutation between cooperators and defectors and selection on two levels: within proto-cells and between proto-cells. We find surprising similarities and differences between models with and without cell death. In both cases, a necessary requirement for group selection to favor some level of cooperation is the continuous formation of a minimum fraction of pure cooperator groups. Subsequently these groups become undermined by defectors, because of mutation and selection within cells. Cell division mechanisms which generate pure cooperator groups more efficiently are stronger promoters of cooperation. For example, division of a proto-cell into many daughter cells is more powerful in enhancing cooperation than division into two daughter cells. Our model differs from previous studies of group selection in that we explore a variety of different features and relax several restrictive assumptions that would be needed for analytic calculations.


Asunto(s)
División Celular , Simulación por Computador , Modelos Biológicos
2.
Nat Commun ; 15(1): 1639, 2024 Feb 22.
Artículo en Inglés | MEDLINE | ID: mdl-38388493

RESUMEN

Recent developments in protein design rely on large neural networks with up to 100s of millions of parameters, yet it is unclear which residue dependencies are critical for determining protein function. Here, we show that amino acid preferences at individual residues-without accounting for mutation interactions-explain much and sometimes virtually all of the combinatorial mutation effects across 8 datasets (R2 ~ 78-98%). Hence, few observations (~100 times the number of mutated residues) enable accurate prediction of held-out variant effects (Pearson r > 0.80). We hypothesized that the local structural contexts around a residue could be sufficient to predict mutation preferences, and develop an unsupervised approach termed CoVES (Combinatorial Variant Effects from Structure). Our results suggest that CoVES outperforms not just model-free methods but also similarly to complex models for creating functional and diverse protein variants. CoVES offers an effective alternative to complicated models for identifying functional protein mutations.


Asunto(s)
Redes Neurales de la Computación , Proteínas , Proteínas/metabolismo , Aminoácidos/química , Mutación
3.
Front Immunol ; 12: 674021, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33986759

RESUMEN

A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, multiplexing and sequencing technologies have accelerated engineering of improved capsid properties such as production yield, packaging efficiency, biodistribution and transduction efficiency. Here we outline how machine learning, advances in viral immunology, and high-throughput measurements can enable engineering of a new generation of de-immunized capsids beyond the antigenic landscape of natural AAVs, towards expanding the therapeutic reach of gene therapy.


Asunto(s)
Cápside/inmunología , Terapia Genética/métodos , Aprendizaje Automático , Animales , Dependovirus , Vectores Genéticos , Humanos
4.
Nat Biotechnol ; 39(6): 691-696, 2021 06.
Artículo en Inglés | MEDLINE | ID: mdl-33574611

RESUMEN

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics.


Asunto(s)
Proteínas de la Cápside/genética , Dependovirus/genética , Aprendizaje Automático , Vectores Genéticos , Células HeLa , Humanos
5.
Nat Commun ; 11(1): 2192, 2020 05 04.
Artículo en Inglés | MEDLINE | ID: mdl-32366844

RESUMEN

Major evolutionary transitions, including the emergence of life, likely occurred in aqueous environments. While the role of water's chemistry in early life is well studied, the effects of water's ability to manipulate population structure are less clear. Population structure is known to be critical, as effective replicators must be insulated from parasites. Here, we propose that turbulent coherent structures, long-lasting flow patterns which trap particles, may serve many of the properties associated with compartments - collocalization, division, and merging - which are commonly thought to play a key role in the origins of life and other evolutionary transitions. We substantiate this idea by simulating multiple proposed metabolisms for early life in a simple model of a turbulent flow, and find that balancing the turnover times of biological particles and coherent structures can indeed enhance the likelihood of these metabolisms overcoming extinction either via parasitism or via a lack of metabolic support. Our results suggest that group selection models may be applicable with fewer physical and chemical constraints than previously thought, and apply much more widely in aqueous environments.


Asunto(s)
Algoritmos , Hidrodinámica , Modelos Teóricos , Agua/química , Evolución Biológica , Fenómenos Biofísicos , Difusión , Movimiento (Física) , Origen de la Vida , Reología , Viscosidad , Agua/metabolismo
6.
Science ; 366(6469): 1139-1143, 2019 11 29.
Artículo en Inglés | MEDLINE | ID: mdl-31780559

RESUMEN

Adeno-associated virus (AAV) capsids can deliver transformative gene therapies, but our understanding of AAV biology remains incomplete. We generated the complete first-order AAV2 capsid fitness landscape, characterizing all single-codon substitutions, insertions, and deletions across multiple functions relevant for in vivo delivery. We discovered a frameshifted gene in the VP1 region that expresses a membrane-associated accessory protein that limits AAV production through competitive exclusion. Mutant biodistribution revealed the importance of both surface-exposed and buried residues, with a few phenotypic profiles characterizing most variants. Finally, we algorithmically designed and experimentally verified a diverse in vivo targeted capsid library with viability far exceeding random mutagenesis approaches. These results demonstrate the power of systematic mutagenesis for deciphering complex genomes and the potential of empirical machine-guided protein engineering.


Asunto(s)
Proteínas de la Cápside/genética , Cápside , Dependovirus/genética , Terapia Genética , Ingeniería de Proteínas/métodos , Genes Virales , Células HEK293 , Humanos , Mutagénesis Insercional , Eliminación de Secuencia , Transfección
7.
J R Soc Interface ; 15(139)2018 02.
Artículo en Inglés | MEDLINE | ID: mdl-29491181

RESUMEN

Compartments are ubiquitous throughout biology, and they have very likely played a crucial role at the origin of life. Here we assume that a protocell, which is a compartment enclosing functional components, requires N such components in order to be evolvable. We calculate the timescale in which a minimal evolvable protocell is produced. We show that when protocells fuse and share information, the timescales polynomially in N By contrast, in the absence of fusion, the worst-case scenario is exponential in N We discuss the implications of this result for the origin of life and other biological processes.


Asunto(s)
Evolución Biológica , Membrana Celular/metabolismo , Modelos Biológicos , Origen de la Vida
8.
PLoS One ; 12(7): e0180208, 2017.
Artículo en Inglés | MEDLINE | ID: mdl-28723913

RESUMEN

The transition from prelife where self-replication does not occur, to life which exhibits self-replication and evolution, has been a subject of interest for many decades. Membranes, forming compartments, seem to be a critical component of this transition as they provide several concurrent benefits. They maintain localized interactions, generate electro-chemical gradients, and help in selecting cooperative functions as they arise. These functions pave the way for the emergence and maintenance of simple metabolic cycles and polymers. In the context of origin of life, evolution of information-carrying molecules and RNA based enzymes within compartments has been subject to intensive theoretical and experimental research. Hence, many experimental efforts aim to produce compartments that contain elongating polynucleotides (also referred to as protocells), which store information and perform catalysis. Despite impressive experimental progress, we are still relatively ignorant about the dynamics by which elongating polynucleotides can produce more sophisticated behaviors. Here we perform computer simulations to couple information production through template-free elongation of polymers with dividing compartments. We find that polymers with a simple ability-biasing the concentration of monomers within their own compartment-can acquire a selective advantage in prelife. We further investigate whether such a mechanism allows for cooperative dynamics to dominate over purely competitive ones. We show that under this system of biased monomer addition, even without template-directed self-replication, genetic motifs can emerge, compete, cooperate, and ultimately survive within the population.


Asunto(s)
Evolución Biológica , Origen de la Vida , Polímeros , Prebióticos , Células Artificiales , Simulación por Computador
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