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Infologs

Infologs is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Infologs rather than just read about it. In short: Infologs are independently designed synthetic genes derived from one or a few genes where substitutions are systematically incorporated to maximize information. Infologs are designed for perfect diversity distribution to maximize search efficiency.

Infologs — main illustration
Infologs — illustration

Key takeaways

  • Infologs belongs to biology; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Infologs to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Infologs from memory before moving on to harder problems.

Reference excerpt

Infologs are independently designed synthetic genes derived from one or a few genes where substitutions are systematically incorporated to maximize information. Infologs are designed for perfect diversity distribution to maximize search efficiency. Typical protein engineering methods rely on screening a high number (106-1012 or more) of gene variants to identify individuals with improved activity using a surrogate high throughput screen (HTP) to identify initial hits. Unfortunately, results are defined by what is screened for, thus the “hit” from the HTP screen often has very little real activity in a lower throughput assay more indicative of the improved functionality for which the protein is being developed. By adapting the standard algorithms for engineering complex systems to work with biological systems, the resulting process enables researchers to deconvolute how substitutions within a protein sequence modify its function. Combining these algorithms with an integrated query and ranking mechanism allows the identification of appropriate sequence substitutions. Infologs refers to the set of designed genes, singular use Infolog describes an individual variant.

Ancestry Homology between protein or DNA sequences is defined in terms of shared ancestry. Two segments of DNA can have shared ancestry because of either a speciation event (orthologs) or a duplication event (paralogs). Homologs are similar genes and/or proteins which are related by ancestry. Orthologs are the 'same' gene, but from different organisms. Homologous sequences are orthologous if they were separated by a speciation event: when a species diverges into two separate species, the copies of a single gene in the two resulting species are said to be orthologous. Orthologs, or orthologous genes, are genes in different species that originated by vertical descent from a single gene of the last common ancestor. The term "ortholog" was coined in 1970 by Walter Fitch. Paralogs are related genes originating from one gene that through duplication ended up as two genes that over time has evolved for two separate functions (or, according to a recent Science paper, a promiscuous starting gene that duplicated and each copy evolved towards different functions). Paralogs typically have the same or similar function, but sometimes do not: due to lack of the original selective pressure upon one copy of the duplicated gene, this copy is free to mutate and acquire new functions. Paralogs usually occur from within the same species. Xenologs are homologs resulting from horizontal gene transfer between two organisms. Xenologs can have different functions, if the new environment is vastly different for the horizontally moving gene. In general, though, xenologs typically have similar function in both organisms. Infologs are similar genes and/or proteins which are related by synthetic ancestry to approach perfect diversity distribution.

Features Optimize directly for function in the final application Does not require high-throughput (HTP) screens Screen small numbers of variants (50-200) directly for the desired function Decreased false positives: variants identified by HTP screens that do not retain activity in 'real' assay Decreased loss of potential positive hits due to screening error or poor correlation between HTP screen and 'real' assay No biodiversity collections required, everything is synthesized as needed Sequence-function relationships provide the basis for strong composition-of-matter patent claims.

Case study Transforming Protein engineering with Infologs: Using independently designed synthetic genes where substitutions are systematically incorporated (Infologs) leads to uniform sampling, systematic variance and unrestricted information rich results. Wheat Glutathione S-transferases (GST) with the ability to detoxify a panel of common herbicides was designed using this patented bioengineering method. The relative functional contribution of 60 amino acid substitutions against 14 herbicides was quantified using only 96 Infologs and dramatically improved by a small set (16) of 2nd generation Infologs. In addition, highly predictable GST sequence-function models against two commercially relevant herbicides were created with quantification of relative functional contribution of 60 amino acid substitutions in two dimensions.

Rational design of proteins

In rational protein design, the scientist uses detailed knowledge of the structure and function of the protein to make desired changes. This generally has the advantage of being technically easy and inexpensive, since site-directed mutagenesis techniques are well-developed. However, its major drawback is that detailed structural knowledge of a protein is often unavailable, and even when it is available, it can be extremely difficult to predict the effects of various mutations. Computational protein design algorithms seek to identify novel amino acid sequences that are low in energy when folded to the pre-specified target structure. While the sequence-conformation space that needs to be searched is large, the most challenging requirement for computational protein design is a fast, yet accurate, energy function that can distinguish optimal sequences from similar suboptimal ones.

See also OrthoDB Protein folding Synthetic biology

References

… excerpt ends here. Continue reading the full article.

Illustrations

Infologs: Infologs show full diversity distribution of space
Infologs show full diversity distribution of space
Infologs illustration
Infologs illustration

Worked examples

Example 1 — a first encounter with Infologs

Start with the simplest possible case. Write down what Infologs claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Infologs before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Infologs ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Infologs

In research
Infologs appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Infologs in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Infologs is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics, Protein engineering, so understanding it makes those chapters shorter.
In everyday life
Look for Infologs outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Infologs in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Infologs means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Infologs out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Infologs in simple terms?

Infologs are independently designed synthetic genes derived from one or a few genes where substitutions are systematically incorporated to maximize information. Infologs are designed for perfect diversity distribution to maximize search efficiency.

Why does Infologs matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Infologs?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Infologs.

Tags

  • Bioinformatics
  • Protein engineering

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