Field of Science

Response to Ambur et al.

 The points in purple are objections raised by Ambur et al. to the hypothesis that the main function of DNA uptake by competent bacteria is acquisition of DNA as a nutrient:

These points are typical of those raised when the goal is to dismiss the nutrient hypothesis rather than to carefully consider all the issues.

(i) As yet, there is no clear evidence that the integration of nucleotides taken up by transformation become routed into DNA metabolism.

Yes. Competence has mainly been studied in mucosal commensals, where investigations of metabolism are difficult.  In these organisms absence of evidence is not evidence of absence.

(ii) The presence of exogenous DNA does not appear to induce competence in any transformable species.

Yes, but I don’t see why this is more relevant for the nutrient hypothesis than for other hypotheses.  (Also, Vibrio does use chitin as a signal for competence; its presence indicates biofilms and abundant DNA.)

(iii) Competence in streptococci, like S. pneumoniae, is induced for only a short time period during exponential growth when other resources are highly abundant.

Because laboratory growth conditions for human commensals and pathogens are so different from natural growth conditions, lab cultures are very poor guides to what matters in the real world.  That’s why our work focused on understanding the regulatory machinery.

(iv) Transported DNA is heavily protected against nuclease digestion within the cell, potentially enabling transported fragments to remain intact as a substrate for recombination.

And yet most competent bacteria take up all DNAs they encounter, and DNA that cannot be recombined is efficiently degraded.  The proteins that protect the DNA are also common in non-competent species and so must function outside of transformation.

(v) The hypothesis does not explain why several competent species only take up DNA from close relatives due to conserved DNA uptake sequences (USS and DUS) despite the fact that non-homologous DNA could be used as a source of nucleotides for direct use or degradation.

On the flip side, almost all competent bacteria take up DNA indiscriminately, so DNA’s benefit can’t depend on its information content.  For these exceptions, we have hypothesized that sequence-dependent uptake constraints exist in these species, and have shown that these create molecular drive that causes uptake sequences to accumulate in genomes at frequencies and distributions corresponding to those seen in real genomes with DUS and USS.

Designing better masks

Optimizing design of masks to prevent spread of COVID-19:

(Originally a series of tweets that came out in the wrong order)

1.     COVID-19 is transmitted mainly by droplets and particles in the air we breathe, not by contact with contaminated surfaces.

2.     Surgical and cloth masks only poorly protect an uninfected wearer from becoming infected. 

3.     But these masks CAN reduce virus release by an infectious person, because exhalation produces large wet droplets that are relatively easy to trap on their way out but that rapidly evaporate to smaller dry particles that are hard to trap on their way in (see Wells Curve). 

4.     So the general public should wear masks not to protect themselves from infection but to protect other members of the community, in case the wearer is unknowingly infected. But design of surgical and cloth face masks has not been optimized for this function. 

5.     What properties should such a mask have?
a.     The fabric should block passage of most respiratory droplets.
b.     Most exhaled air should pass through the mask, not around it, even after a cough or sneeze.
c.      Any exhaled air that escapes should escape downward, not upward.
d.     Air and water molecules should pass easily through the mask fabric.
e.     For ease of breathing, exhaled and inhaled air should be filtered over a large area of mask. The mask should not be tightly pressed to the nostrils and mouth.
f.      To maximize air exchange, the mask should not normally enclose a large volume of air.
g.     The space inside the mask should expand in the event of a cough or sneeze, to trap the large volume of air and allow it to be gradually released through the mask (not around it). 

6.     These goals may best be met by long lightweight scarf-type masks that fit snugly around the nose, cheeks and ears, and settle loosely on the shoulders. 

A semi-quantitative framework for long-term thinking about the COVID-19 pandemic

I think the current rush to invoke extreme flatten-the-curve measures needs to be accompanied by careful thought about what we'll do once the measures have had the desired effect.  In particular, how long would restrictive measures need to remain in force, and how will we decide when they can be lifted?  And how can we mitigate the personal, social and economic harms of the measures while they remain in place?

So I've created a series of semi-quantitative graphs to help.  ('Semi-quantitative means that there are numbers on the axes and specific doubling times for periods of exponential growth, but the finer details are rough approximations.)

Here's the tl;dr for the first 6 months:

Points to note:  

  • The Y-axis is log-scale, so small differences in height indicate big differences in numbers of infected people.
  • Five different scenarios are considered, with plausible effects on doubling time of % infected.
  • Restrictive measures are assumed to reduce peak % infected and eventual equilibrium.
  • For all but the most extreme scenario, infection levels remain high (≥1%) even after 6 months.
  • It will be very hard to justify lifting restrictions that have been effective.

Here's the tl;dr if the costly restrictions are lifted after 7 months of misery:

Points to note:
  • In all cases, lifting restrictions makes % infected much worse (remember, log-scale...).
  • The more effective the restrictions were in limiting total infections, the worse the second wave on infection is, and the longer it drags on.
Below are the individual graphs:

If no action were taken (doubling time 3 days):

Infections are assumed to peak at about 30% of the population at weeks 6-10, and then to decline to about 1% of the population since about half of the population will remain susceptible.

If we take actions that have no or low personal cost (doubling time 6 days):
  • Reduce physical contact with other people
  • Don’t touch your face
  • Wash your hands
  • Avoid large groups and crowded places
  • Work from home if this is possible
  • Reduce travel

The peak % infected is lower, maybe 20%,  occurs at weeks 11-16, and declines to about 0.3% provided the restrictions remain in place.

If we take actions that have moderate cost (doubling time 10 days):

  • Cancel pro-sports, concerts, conferences and other large gatherings
  • Close bars and restaurants
  • Cancel university classes

The peak % infected is lower, maybe 15%, occurs at weeks 18-25, and declines to about 0.15% provided the restrictions remain in place.

If we take actions that have high cost (doubling time 20 days):

  • Close all schools and universities
  • Close close non-essential shops and workplaces
  • Close all public buildings
  • Ban all non-essential travel

The peak % infected is lower, about 10%%, occurs at weeks 35-40, and falls to about 1% by week 52 provided the restrictions remain in place.

If we take extreme actions (R0 <1 b="">

  • Lock down the entire population
  • Enforce by police or the National Guard

The % infected slows its increase and begins to decline by week 15.  It continues declining provided the restrictions remain in place.