Sequence-dependent configuration changes and condensation of double-stranded poly(dG-dC).(dG-dC) (GC-DNA) and ds poly(dA-dT).(dA-dT) (AT-DNA) were observed by atomic force microscopy in the presence of Ni(II). Less condensing agent was required to generate configuration changes in GC-DNA as compared to AT-DNA. In the presence of Ni(II) cations, GC-DNA adopted a Z-type conformation and underwent a stepwise condensation, starting with partial intramolecular folding, followed by intermolecular condensation of two to several molecules and ending with the formation of toroids, rods, and jumbles. GC-DNA condensates were unusual in that the most highly condensed regions were surrounded by loops of ds GC-DNA. In contrast, AT-DNA retained its B-type conformation and displayed only minor condensation even at high Ni(II) concentrations. The Ni(II)-dependent differences in condensation between GC-DNA and AT-DNA are predicted by an extension of the electrostatic zipper motif proposed by Kornyshev and Leikin, in which we account for shorter than Debye screening length surface separations between the DNA molecules and for the Ni(II)-induced conformation change of GC-DNA to Z-DNA.

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The lack of widespread COVID-19 testing and the prevalence of asymptomatic infections have been major factors in the current pandemic. Despite the improvements in clinical testing, as we move toward reopening USA, widespread surveillance testing becomes critical. Academic (nonmedical) labs can help provide such testing; the CDC-approved guidelines for COVID-19 testing require routine equipment and protocols that are commonly used in academic research labs around the country. Faculty at the authors' institution were successfully able to test asymptomatic students for COVID-19. By empowering nonmedical academic scientists with preexisting knowledge, expertise with the protocols, and access to the instruments, an additional 1.2-3.5 million COVID-19 tests could be processed each day at local universities and academic labs.SARS-CoV-2, the causative agent for COVID-19 continues to decimate high-risk populations, cripple economies and stress an overtaxed medical system. On the front lines, medical personnel plead for increased personal protective equipment, more test kits and faster turnaround times. With this highly communicable virus, rapid testing is essential to identifying and isolating infected individuals, slowing the spread and containing the disease. Some countries, such as South Korea and Iceland, implemented widespread testing of their populations, resulting in less cases, fewer fatalities and an intact economy [1]. This inverse relationship, whereby increased COVID-19 testing leads to decreased impacts on society, means businesses and schools can reopen safely and the public health concerns remain low because the presumptive infection status of each individual is known, regardless of disease severity. Recent studies of complete populations on cruise ships and isolated aircraft carriers have shown that up to 50% of cases are asymptomatic [2][3][4]. These individuals do not have symptoms and therefore may not be isolating, further spreading the virus to individuals who may not be so fortunate. Despite this important, poorly understood population of asymptomatic individuals, the scarcity of reagents and the testing backlog in overworked diagnostic labs currently limits testing to symptomatic individuals. According to CDC guidelines, only hospitalized patients (Priority 1) and healthcare workers (Priority 3) are tested if asymptomatic [5]. With calls for the economy to reopen, implementation of robust testing could reduce the potential risk for a resurgent outbreak [6]. Large-scale testing programs can be (and have been) instrumental in identifying asymptomatic and presymptomatic carriers, yet this approach comes down to capacity: who will perform these tests and how will they do it? In a time of social media, crowdsourcing, citizen scientists and resource pooling, one invaluable group remarkably remains overlooked: the nonmedical academic scientist.Early in the pandemic, efforts at universities in California [7] and Washington [8] proved the utility of research labs performing large, wide-scale testing in thei...

Robust surveillance testing is a key strategic plan to prevent COVID-19 outbreaks and slow the spread of the SARS-CoV-2 pandemic; however, limited resources, facilities and time often impair the implementation of a widespread surveillance effort. To mitigate these resource limitations, we employed a strategy of pooling samples, reducing reagent cost and processing time. Through utilizing academic faculty and labs, successful pooled surveillance testing was conducted throughout Fall 2020 semester to detect positive SARS-CoV-2 infections in a population of 4400 students. During the semester, over 25,000 individual COVID status evaluations were made by pooling eight individual samples into one quantitative reverse transcription polymerase chain reaction. This pooled surveillance strategy was highly effective at detecting infection and significantly reduced financial burden and cost by $3.6 million.