Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond

Selberg, Avery G. A.; Gaucher, Eric A.; Liberles, David A.

doi:10.1007/s00239-021-09993-1

Cited by 39 publications

(35 citation statements)

References 76 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We have also extended the biomedical utility of ancient proteins to treat/prevent diseases. 32 , 33 , 34 , 35 We further anticipate that future studies will provide more insights into the advantages and/or disadvantages of uric acid’s role as a critical antioxidant and its connection to the loss of vitamin C synthesis in the Haplorhini clade of mammals (tarsiers, monkeys, and apes). 5 , 6 , 8 , 36 , 37 …”

Section: Discussionmentioning

confidence: 99%

CRISPR-Cas9-mediated reactivation of the uricase pseudogene in human cells prevents acute hyperuricemia

Balico

Gaucher

2021

Molecular Therapy - Nucleic Acids

Self Cite

View full text Add to dashboard Cite

The utility of CRISPR-Cas9 to repair or reverse diseased states that arise from recent genetic mutations in the human genome is now widely appreciated. The use of CRISPR to “design” the outcomes of biology is challenged by both specialized ethicists and the general public. Less of a focus, however, is the ability of CRISPR to provide metabolic supplements or prophylactic molecules that improve long-term human health by overwriting ancient evolutionary events. Here, we use CRISPR to genomically integrate a functional uricase gene that encodes an enzymatically active protein into the human genome. These uricase-producing cells are able to reduce or even eliminate high concentrations of exogenous uric acid despite the enzyme being localized to peroxisomes. Our evolutionary engineered cells represent the first instance of the primate ape lineage expressing a functional uricase encoded in the genome within the last 20 million years. We anticipate that human cells expressing uricase will help prevent hyperuricemia (including gout) as well as hypertension and will help protect against fatty liver disease in the future.

show abstract

Section: Discussionmentioning

confidence: 99%

CRISPR-Cas9-mediated reactivation of the uricase pseudogene in human cells prevents acute hyperuricemia

Balico

Gaucher

2021

Molecular Therapy - Nucleic Acids

Self Cite

View full text Add to dashboard Cite

show abstract

“…Enzymes obtained from ASR make attractive starting points for enzyme design as they tend to be highly thermostable, conformationally flexible, and evolvable [19][20][21]. While many different computational algorithms exist with which to perform ASR (Table 1), the basic principle of all of these is to use the sequences of known, extant proteins to reconstruct phylogenetic trees containing sequences of putative ancestors, based on the probability of finding a given amino acid substitution at the given point in amino acid sequence [22,23]. Such ancestral inference yields a 'cloud' of sequences that relate to putative historical ancestors [24][25][26], although typically only the most probabilistic of these sequences is subject to further experimental or computational characterization of the evolutionary trajectory.…”

Section: Repurposing Ancient Enzymes For New Catalytic Functionsmentioning

confidence: 99%

“…Clearly, however, while there are challenges in inferring actual evolutionary information through the use of ASR, what is obvious is that protein scaffolds obtained through ASR are excellent starting points for subsequent protein design effort due to their high thermostability and evolvability [31]. There have been a great number of experimental studies using ancestrally reconstructed proteins for enzyme design due to their greater thermostability; more recently, interest has also shifted to using ASR to obtain scaffolds that can be used as starting points for the engineering of catalytic properties [22,23,27,31]. Several such studies have focused specifically on using ASR to obtain flexible scaffolds that can be manipulated for engineering purposes in terms of their conformational properties.…”

Section: Repurposing Ancient Enzymes For New Catalytic Functionsmentioning

confidence: 99%

Exploiting enzyme evolution for computational protein design

Pinto¹,

Corbella²,

Demkiv³

et al. 2022

Trends in Biochemical Sciences

View full text Add to dashboard Cite

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies. Computational enzyme design based on protein evolution: an overviewRoughly three decades have passed since the first attempts to design new enzymes using computational approaches [1,2], and the field has matured considerably since then. While the earliest attempts at computational enzyme design focused primarily on side-chain positioning [1][2][3][4] or on focusing the search space for in vitro directed evolution (see Glossary) studies [5], subsequent work broadly expanded the scope of the field, including the fully de novo design of new enzymes [6] (typically followed by optimization using directed evolution) and the repurposing of existing enzymes to catalyze ever more complex chemical reactions [7,8]. In addition, computational design approaches are becoming ever-more streamlined, such that there now exists a range of powerful web servers that can assist in the design process [9].In principle, computational design approaches can take two very loosely defined directions: structure-based design approaches that require some level of knowledge of the system of interest, including information about the chemical mechanisms, transition states, and key catalytic residues involved; and sequence-based design approaches that can, for example, draw on evolutionary information to predict potential hotspots for protein engineering as well as new variants with desired physicochemical properties, something that is in particular increasingly being achieved using machine-learning approaches [10].Computational approaches that require minimal knowledge of the molecular details of the chemical processes involved are attractive for their speed and efficiency, as exploring the underlying mechanisms and transition states typically requires significant experimental and/or computational effort. However, much like their experimental counterparts, such approaches are likely to hit optimization plateaus [11,12] where further improvement in activity becomes extremely challenging, and without knowledge of the underlying chemistry it can be difficult-to-impossible to overcome such plateaus. Therefore, rather than competing with each other, sequence-and structure-based approaches are highly complementary as each provides different type...

show abstract

“…Ancestral sequence reconstruction (ASR) uses phylogenetic analyses and sequences of modern protein homologs to compute statistically plausible approximations to the corresponding ancestral sequences 10,11 . During the last ~25 years, proteins encoded by reconstructed sequences ("resurrected" ancestral proteins) have been widely used as tools to address important problems in molecular evolution [12][13][14][15][16] . They have also been found to provide new possibilities for protein biomedical applications and protein engineering [17][18][19][20][21] .…”

Section: Introductionmentioning

confidence: 99%

Combining ancestral reconstruction with folding-landscape simulations to engineer heterologous protein expression

Gamiz-Arco

Risso

Gaucher

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Obligate symbionts exhibit high evolutionary rates and extensive sequence divergence. Here, we use the thioredoxin from Candidatus Photodesmus katoptron, an uncultured symbiont of flashlight fish, to explore evolutionary and engineering aspects of protein folding in heterologous hosts. The symbiont protein is a standard thioredoxin in terms of 3D-structure, stability and redox activity. However, its refolding in vitro is very slow and its expression in E. coli leads to insoluble protein. By contrast, resurrected Precambrian thioredoxins express efficiently in E. coli, plausibly reflecting an ancient adaptation to unassisted folding. We have used a statistical-mechanical model of the folding landscape to guide back-to-ancestor engineering of the symbiont protein. Remarkably, we find that the efficiency of heterologous expression correlates with the in vitro refolding rate and that the ancestral expression efficiency can be achieved with only 1-2 back-to-ancestor replacements. These results demonstrate a sequence-engineering approach to rescue inefficient heterologous expression, a major biotechnological bottleneck.

show abstract

Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond

Cited by 39 publications

References 76 publications

CRISPR-Cas9-mediated reactivation of the uricase pseudogene in human cells prevents acute hyperuricemia

CRISPR-Cas9-mediated reactivation of the uricase pseudogene in human cells prevents acute hyperuricemia

Exploiting enzyme evolution for computational protein design

Combining ancestral reconstruction with folding-landscape simulations to engineer heterologous protein expression

Contact Info

Product

Resources

About